diff --git a/.gitignore b/.gitignore index 97d79731..996fc5d8 100644 --- a/.gitignore +++ b/.gitignore @@ -2,6 +2,11 @@ docs/equations/*.aux docs/equations/*.log docs/equations/*.out docs/equations/*.synctex.gz +code/ch12/mnist +code/datasets/mnist/t10k-images-idx3-ubyte +code/datasets/mnist/t10k-labels-idx1-ubyte +code/datasets/mnist/train-images-idx3-ubyte +code/datasets/mnist/train-labels-idx1-ubyte .ipynb_checkpoints .DS_Store diff --git a/README.md b/README.md index eef19b78..13ce8fd4 100644 --- a/README.md +++ b/README.md @@ -1,59 +1,48 @@ -# python-machine-learning-book +# Python Machine Learning book code repository -*Python Machine Learning* code repository. -What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and -we will put those concepts into action mainly using NumPy, scikit-learn, and Theano. - -You are not sure if this book is for you? Please checkout the excerpts from the [Foreword](./docs/foreword_ro.pdf) and [Preface](./docs/preface_sr.pdf), or take a look at the [FAQ](#faq) section for further information. +[![Google Group](https://img.shields.io/badge/-Google%20Group-lightgrey.svg)](https://groups.google.com/forum/#!forum/python-machine-learning-reader-discussion-board) --- -![](./images/pymle_cover_small.jpg) +#### IMPORTANT NOTE (09/21/2017): -
-1st edition, published September 23rd 2015
-Paperback: 454 pages
-Publisher: Packt Publishing
-Language: English
-ISBN-10: 1783555130
-ISBN-13: 978-1783555130
-Kindle ASIN: B00YSILNL0
- - -### [Feedback & Reviews](./docs/feedback.md) - -[ ![](./images/pymle_amzn.png)](./docs/feedback.md) +This GitHub repository contains the code examples of the **1st Edition** of Python Machine Learning book. If you are looking for the code examples of the **2nd Edition**, please refer to [this](https://github.com/rasbt/python-machine-learning-book-2nd-edition#whats-new-in-the-second-edition-from-the-first-edition) repository instead. --- -> *Sebastian Raschka’s new book, Python Machine Learning, has just been released. I got a chance to read a review copy and it’s just as I expected - really great! It’s well organized, super easy to follow, and it not only offers a good foundation for smart, non-experts, practitioners will get some ideas and learn new tricks here as well.* -– Lon Riesberg at [Data Elixir](http://dataelixir.com/issues/55#start) -> *Superb job! Thus far, for me it seems to have hit the right balance of theory and practice…math and code!* -– [Brian Thomas](http://sebastianraschka.com/blog/2015/writing-pymle.html#comment-2295668894) +What you can expect are 400 pages rich in useful material just about everything you need to know to get started with machine learning ... from theory to the actual code that you can directly put into action! This is not yet just another "this is how scikit-learn works" book. I aim to explain all the underlying concepts, tell you everything you need to know in terms of best practices and caveats, and +we will put those concepts into action mainly using NumPy, scikit-learn, and Theano. -> *I've read (virtually) every Machine Learning title based around Scikit-learn and this is hands-down the best one out there.* -– [Jason Wolosonovich](https://www.linkedin.com/pulse/python-machine-learning-sebastian-raschka-review-jason-wolosonovich?trk=prof-post) +You are not sure if this book is for you? Please checkout the excerpts from the [Foreword](./docs/foreword_ro.pdf) and [Preface](./docs/preface_sr.pdf), or take a look at the [FAQ](#faq) section for further information. -## Links +--- -- ebook and paperback at [Amazon.com](http://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/ref=sr_1_2?ie=UTF8&qid=1437754343&sr=8-2&keywords=python+machine+learning+essentials), [Amazon.co.uk](http://www.amazon.co.uk/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130), [Amazon.de](http://www.amazon.de/s/ref=nb_sb_noss_2?__mk_de_DE=ÅMÅŽÕÑ&url=search-alias%3Daps&field-keywords=python+machine+learning) -- [ebook and paperback](https://www.packtpub.com/big-data-and-business-intelligence/python-machine-learning) from Packt (the publisher) -- at other book stores: [Google Books](https://books.google.com/books?id=GOVOCwAAQBAJ&source=gbs_slider_cls_metadata_7_mylibrary), [O'Reilly](http://shop.oreilly.com/product/9781783555130.do), [Safari](https://www.safaribooksonline.com/library/view/python-machine-learning/9781783555130/), [Barnes & Noble](http://www.barnesandnoble.com/w/python-machine-learning-essentials-sebastian-raschka/1121999969?ean=9781783555130), [Apple iBooks](https://itunes.apple.com/us/book/python-machine-learning/id1028207310?mt=11), ... -- social platforms: [Goodreads](https://www.goodreads.com/book/show/25545994-python-machine-learning) +[![](./images/pymle_cover_double_small.jpg)](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/ref=sr_1_1?ie=UTF8&qid=1470882464&sr=8-1&keywords=python+machine+learning) -#### Translations +1st edition, published September 23rd 2015
+Paperback: 454 pages
+Publisher: Packt Publishing
+Language: English
+ISBN-10: 1783555130
+ISBN-13: 978-1783555130
+Kindle ASIN: B00YSILNL0
-- [German translation](https://www.amazon.de/Machine-Learning-Python-mitp-Professional/dp/3958454224/) via “mitp Verlag” -- [Japanese translation](http://www.amazon.co.jp/gp/product/4844380605/) via “Impress Top Gear” +
-![](./images/ml-overview.jpg) +[![](./images/CRBadgeNotableBook.jpg)](http://www.computingreviews.com/recommend/bestof/notableitems.cfm?bestYear=2016) -### [Literature References & Further Reading Resources](./docs/references.md) +
-### [Errata](./docs/errata.md) +German ISBN-13: 978-3958454224
+Japanese ISBN-13: 978-4844380603
+Italian ISBN-13: 978-8850333974
+Chinese (traditional) ISBN-13: 978-9864341405
+Chinese (mainland) ISBN-13: 978-7111558804
+Korean ISBN-13: 979-1187497035
+Russian ISBN-13: 978-5970604090
@@ -85,11 +74,124 @@ Simply click on the `ipynb`/`nbviewer` links next to the chapter headlines to vi
-- Equation Reference [[PDF](./docs/equations/pymle-equations.pdf)] [[TEX](./docs/equations/pymle-equations.tex)] +#### Equation Reference -
+ + +[[PDF](./docs/equations/pymle-equations.pdf)] [[TEX](./docs/equations/pymle-equations.tex)] + +#### Slides for Teaching + +A big thanks to [Dmitriy Dligach](dmitriydligach) for sharing his slides from his machine learning course that is currently offered at [Loyola University Chicago](http://www.luc.edu/cs/). + +- [https://github.com/dmitriydligach/PyMLSlides](https://github.com/dmitriydligach/PyMLSlides) +- + + + +#### Additional Math and NumPy Resources + +Some readers were asking about Math and NumPy primers, since they were not included due to length limitations. However, I recently put together such resources for another book, but I made these *chapters* freely available online in hope that they also serve as helpful background material for this book: + + +- Algebra Basics [[PDF](https://sebastianraschka.com/pdf/books/dlb/appendix_b_algebra.pdf)] [[EPUB](https://sebastianraschka.com/pdf/books/dlb/appendix_b_algebra.epub)] + +- A Calculus and Differentiation Primer [[PDF](https://sebastianraschka.com/pdf/books/dlb/appendix_d_calculus.pdf)] [[EPUB](https://sebastianraschka.com/pdf/books/dlb/appendix_d_calculus.epub)] + +- Introduction to NumPy [[PDF](https://sebastianraschka.com/pdf/books/dlb/appendix_f_numpy-intro.pdf)] [[EPUB](https://sebastianraschka.com/pdf/books/dlb/appendix_f_numpy-intro.epub)] [[Code Notebook](https://github.com/rasbt/deep-learning-book/blob/master/code/appendix_f_numpy-intro/appendix_f_numpy-intro.ipynb)] + + + +--- + +#### Citing this Book + +You are very welcome to re-use the code snippets or other contents from this book +in scientific publications and other works; +in this case, I would appreciate citations to the original source: + +**BibTeX**: + +``` +@Book{raschka2015python, + author = {Raschka, Sebastian}, + title = {Python Machine Learning}, + publisher = {Packt Publishing}, + year = {2015}, + address = {Birmingham, UK}, + isbn = {1783555130} + } +``` -**Bonus Notebooks (not in the book)** + +**MLA**: + + +Raschka, Sebastian. *Python machine learning*. Birmingham, UK: Packt Publishing, 2015. Print. + +--- + +### [Feedback & Reviews](./docs/feedback.md) + +#### [Short review snippets](./docs/feedback.md) + +[![](./images/pymle_amzn.png)](https://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/ref=sr_1_1?ie=UTF8&qid=1472342570&sr=8-1&keywords=sebastian+raschka) + +--- +> *Sebastian Raschka’s new book, Python Machine Learning, has just been released. I got a chance to read a review copy and it’s just as I expected - really great! It’s well organized, super easy to follow, and it not only offers a good foundation for smart, non-experts, practitioners will get some ideas and learn new tricks here as well.* +– Lon Riesberg at [Data Elixir](http://dataelixir.com/issues/55#start) + +> *Superb job! Thus far, for me it seems to have hit the right balance of theory and practice…math and code!* +– [Brian Thomas](http://sebastianraschka.com/blog/2015/writing-pymle.html#comment-2295668894) + +> *I've read (virtually) every Machine Learning title based around Scikit-learn and this is hands-down the best one out there.* +– [Jason Wolosonovich](https://www.linkedin.com/pulse/python-machine-learning-sebastian-raschka-review-jason-wolosonovich?trk=prof-post) + +> *The best book I've seen to come out of PACKT Publishing. This is a very well written introduction to machine learning with Python. As others have noted, a perfect mixture of theory and application.* +– [Josh D.](https://www.amazon.com/gp/customer-reviews/R27WB1GWTNGIR2/ref=cm_cr_getr_d_rvw_ttl?ie=UTF8&ASIN=1783555130) + +> *A book with a blend of qualities that is hard to come by: combines the needed mathematics to control the theory with the applied coding in Python. Also great to see it doesn't waste paper in giving a primer on Python as many other books do just to appeal to the greater audience. You can tell it's been written by knowledgeable writers and not just DIY geeks.* +– [Amazon Customer](https://www.amazon.com/gp/customer-reviews/RZWY4TF66Z6V0/ref=cm_cr_getr_d_rvw_ttl?ie=UTF8&ASIN=1783555130) + +> *Sebastian Raschka created an amazing machine learning tutorial which combines theory with practice. The book explains machine learning from a theoretical perspective and has tons of coded examples to show how you would actually use the machine learning technique. It can be read by a beginner or advanced programmer.* +- William P. Ross, [7 Must Read Python Books](http://williampross.com/7-must-read-python-books/) + +#### Longer reviews + +If you need help to decide whether this book is for you, check out some of the "longer" reviews linked below. (If you wrote a review, please let me know, and I'd be happy to add it to the list). + +- [Python Machine Learning Review](http://www.bcs.org/content/conWebDoc/55586) by Patrick Hill at the Chartered Institute for IT +- [Book Review: Python Machine Learning by Sebastian Raschka](http://whatpixel.com/python-machine-learning-book-review/) by Alex Turner at WhatPixel + +--- + +## Links + +- ebook and paperback at [Amazon.com](http://www.amazon.com/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130/ref=sr_1_2?ie=UTF8&qid=1437754343&sr=8-2&keywords=python+machine+learning+essentials), [Amazon.co.uk](http://www.amazon.co.uk/Python-Machine-Learning-Sebastian-Raschka/dp/1783555130), [Amazon.de](http://www.amazon.de/s/ref=nb_sb_noss_2?__mk_de_DE=ÅMÅŽÕÑ&url=search-alias%3Daps&field-keywords=python+machine+learning) +- [ebook and paperback](https://www.packtpub.com/big-data-and-business-intelligence/python-machine-learning) from Packt (the publisher) +- at other book stores: [Google Books](https://books.google.com/books?id=GOVOCwAAQBAJ&source=gbs_slider_cls_metadata_7_mylibrary), [O'Reilly](http://shop.oreilly.com/product/9781783555130.do), [Safari](https://www.safaribooksonline.com/library/view/python-machine-learning/9781783555130/), [Barnes & Noble](http://www.barnesandnoble.com/w/python-machine-learning-essentials-sebastian-raschka/1121999969?ean=9781783555130), [Apple iBooks](https://itunes.apple.com/us/book/python-machine-learning/id1028207310?mt=11), ... +- social platforms: [Goodreads](https://www.goodreads.com/book/show/25545994-python-machine-learning) + +#### Translations + +- [Italian translation](https://www.amazon.it/learning-Costruire-algoritmi-generare-conoscenza/dp/8850333978/) via "Apogeo" +- [German translation](https://www.amazon.de/Machine-Learning-Python-mitp-Professional/dp/3958454224/) via "mitp Verlag" +- [Japanese translation](http://www.amazon.co.jp/gp/product/4844380605/) via "Impress Top Gear" +- [Chinese translation (traditional Chinese)](https://taiwan.kinokuniya.com/bw/9789864341405) +- [Chinese translation (simple Chinese)](https://book.douban.com/subject/27000110/) +- [Korean translation](http://www.kyobobook.co.kr/product/detailViewKor.laf?mallGb=KOR&ejkGb=KOR&barcode=9791187497035) via "Kyobo" +- [Polish translation](https://www.amazon.de/Python-Uczenie-maszynowe-Sebastian-Raschka/dp/8328336138/ref=sr_1_11?ie=UTF8&qid=1513601461&sr=8-11&keywords=sebastian+raschka) via "Helion" + +--- + +### [Literature References & Further Reading Resources](./docs/references.md) + +### [Errata](./docs/errata.md) + + +--- + +### Bonus Notebooks (not in the book) - Logistic Regression Implementation [[dir](./code/bonus)] [[ipynb](./code/bonus/logistic_regression.ipynb)] [[nbviewer](http://nbviewer.ipython.org/github/rasbt/python-machine-learning-book/blob/master/code/bonus/logistic_regression.ipynb)] - A Basic Pipeline and Grid Search Setup [[dir](./code/bonus)] [[ipynb](./code/bonus/svm_iris_pipeline_and_gridsearch.ipynb)] [[nbviewer](http://nbviewer.ipython.org/github/rasbt/python-machine-learning-book/blob/master/code/bonus/svm_iris_pipeline_and_gridsearch.ipynb)] @@ -101,16 +203,25 @@ Simply click on the `ipynb`/`nbviewer` links next to the chapter headlines to vi
-**"Bonus Content" (not in the book)** +**"Related Content" (not in the book)** - [Model evaluation, model selection, and algorithm selection in machine learning - Part I](http://sebastianraschka.com/blog/2016/model-evaluation-selection-part1.html) +- [Model evaluation, model selection, and algorithm selection in machine learning - Part II](http://sebastianraschka.com/blog/2016/model-evaluation-selection-part2.html) +- [Model evaluation, model selection, and algorithm selection in machine learning - Part III](http://sebastianraschka.com/blog/2016/model-evaluation-selection-part3.html) --- +#### SciPy 2016 + We had such a great time at [SciPy 2016](http://scipy2016.scipy.org/ehome/index.php?eventid=146062&tabid=332930&) in Austin! It was a real pleasure to meet and chat with so many readers of my book. Thanks so much for all the nice words and feedback! And in case you missed it, Andreas Mueller and I gave an **Introduction to Machine Learning with Scikit-learn**; if you are interested, the video recordings of [Part I](https://www.youtube.com/watch?v=OB1reY6IX-o&index=91&list=PLYx7XA2nY5Gf37zYZMw6OqGFRPjB1jCy6) and [Part II](https://www.youtube.com/watch?v=Cte8FYCpylk&list=PLYx7XA2nY5Gf37zYZMw6OqGFRPjB1jCy6&index=90) are now online! [![](images/scipy2016.jpg)](https://www.youtube.com/watch?v=OB1reY6IX-o&index=91&list=PLYx7XA2nY5Gf37zYZMw6OqGFRPjB1jCy6) +#### PyData Chicago 2016 + +I attempted the rather challenging task of introducing scikit-learn & machine learning in *just* 90 minutes at PyData Chicago 2016. The slides and tutorial material are available at "[Learning scikit-learn -- An Introduction to Machine Learning in Python](https://github.com/rasbt/pydata-chicago2016-ml-tutorial)." + + --- **Note** @@ -126,8 +237,14 @@ I have set up a separate library, [`mlxtend`](http://rasbt.github.io/mlxtend/), ### Translations +[![](./images/pymle-cover_it.jpg)](https://www.amazon.it/learning-Costruire-algoritmi-generare-conoscenza/dp/8850333978/) [![](./images/pymle-cover_de.jpg)](https://www.amazon.de/Machine-Learning-Python-mitp-Professional/dp/3958454224/) [![](./images/pymle-cover_jp.jpg)](http://www.amazon.co.jp/gp/product/4844380605/) +[![](./images/pymle-cover_cn.jpg)](https://taiwan.kinokuniya.com/bw/9789864341405) +[![](./images/pymle-cover_cn_mainland.jpg)](https://book.douban.com/subject/27000110/) +[![](./images/pymle-cover_kr.jpg)](http://www.kyobobook.co.kr/product/detailViewKor.laf?ejkGb=KOR&mallGb=KOR&barcode=9791187497035&orderClick=LEA&Kc=) +[![](./images/pymle-cover_ru.jpg)](http://www.ozon.ru/context/detail/id/140152222/) +[![](./images/pymle-cover_pl.jpg)](https://www.amazon.de/Python-Uczenie-maszynowe-Sebastian-Raschka/dp/8328336138/ref=sr_1_11?ie=UTF8&qid=1513601461&sr=8-11&keywords=sebastian+raschka)
@@ -149,6 +266,15 @@ In addition, some of you asked me about a platform for readers to discuss the co --- +## Examples and Applications by Readers + +Once again, I have to say (big!) THANKS for all the nice feedback about the book. I've received many emails from readers, who +put the concepts and examples from this book out into the real world and make good use of them in their projects. In this section, I am +starting to gather some of these great applications, and I'd be more than happy to add your project to this list -- just shoot me a quick mail! + +- [40 scripts on Optical Character Recognition](https://github.com/rrlyman/PythonMachineLearingExamples) by [Richard Lyman](https://github.com/rrlyman) +- [Code experiments](https://github.com/jeremyn/python-machine-learning-book) by [Jeremy Nation](https://github.com/jeremyn) +- [What I Learned Implementing a Classifier from Scratch in Python](http://www.jeannicholashould.com) by [Jean-Nicholas Hould](http://www.jeannicholashould.com) ## FAQ @@ -167,6 +293,7 @@ In addition, some of you asked me about a platform for readers to discuss the co ### Questions about the Machine Learning Field +- [How are Artificial Intelligence and Machine Learning related?](./faq/ai-and-ml.md) - [What are some real-world examples of applications of machine learning in the field?](./faq/ml-examples.md) - [What are the different fields of study in data mining?](./faq/datamining-overview.md) - [What are differences in research nature between the two fields: machine learning & data mining?](./faq/datamining-vs-ml.md) @@ -201,6 +328,7 @@ In addition, some of you asked me about a platform for readers to discuss the co ##### Model evaluation - [What is overfitting?](./faq/overfitting.md) +- [How can I avoid overfitting?](./faq/avoid-overfitting.md) - [Is it always better to have the largest possible number of folds when performing cross validation?](./faq/number-of-kfolds.md) - [When training an SVM classifier, is it better to have a large or small number of support vectors?](./faq/num-support-vectors.md) - [How do I evaluate a model?](./faq/evaluate-a-model.md) @@ -218,7 +346,7 @@ In addition, some of you asked me about a platform for readers to discuss the co - [Does regularization in logistic regression always results in better fit and better generalization?](./faq/regularized-logistic-regression-performance.md) - [What is the major difference between naive Bayes and logistic regression?](./faq/naive-bayes-vs-logistic-regression.md) - [What exactly is the "softmax and the multinomial logistic loss" in the context of machine learning?](./faq/softmax.md) -- [What is the relation between Loigistic Regression and Neural Networks and when to use which?](./faq/logisticregr-neuralnet.md) +- [What is the relation between Logistic Regression and Neural Networks and when to use which?](./faq/logisticregr-neuralnet.md) - [Logistic Regression: Why sigmoid function?](./faq/logistic-why-sigmoid.md) - [Is there an analytical solution to Logistic Regression similar to the Normal Equation for Linear Regression?](./faq/logistic-analytical.md) @@ -301,7 +429,7 @@ In addition, some of you asked me about a platform for readers to discuss the co - [Why do you use so many leading and trailing underscores in the code examples?](./faq/underscore-convention.md) - [What is the purpose of the `return self` idioms in your code examples?](./faq/return_self_idiom.md) - [Are there any prerequisites and recommended pre-readings?](./faq/prerequisites.md) - +- [How can I apply SVM to categorical data?](./faq/svm_for_categorical.md) ## Contact @@ -310,11 +438,3 @@ I am happy to answer questions! Just write me an [email](mailto:mail@sebastianra or consider asking the question on the [Google Groups Email List](https://groups.google.com/forum/#!forum/python-machine-learning-book). If you are interested in keeping in touch, I have quite a lively twitter stream ([@rasbt](https://twitter.com/rasbt)) all about data science and machine learning. I also maintain a [blog](http://sebastianraschka.com/articles.html) where I post all of the things I am particularly excited about. - - ---- - -### What's Next - -- [SciPy 2016](http://scipy2016.scipy.org/ehome/index.php?eventid=146062&tabid=332930&) in Austin, Texas is coming up soon. I am really excited to teach the [scikit-learn tutorial session](https://www.eiseverywhere.com/ehome/146062/332960/) with [Andreas Mueller](http://amueller.github.io/) on July 12th this year! I am looking forward to seeing & meeting you all there! -- I have received a bunch of emails lately, and YES, I am really looking forward to writing a new book! Deep learning is the topic that excites me most at the moment, but I think that building up the math background in an interesting, engaging way may be time well spent?! I've been brainstorming lately, and a "Think Machine Learning" series may be a cool idea. I am planning to write about calculus, linear algebra, probability theory, statistics, and all the other puzzle pieces to assemble the big picture: Deep learning. So, stay tuned while I am [getting started!](https://leanpub.com/ml-precalc) :) diff --git a/code/README.md b/code/README.md index 636fc72b..02f17e16 100644 --- a/code/README.md +++ b/code/README.md @@ -1,10 +1,23 @@ -## Table of Contents and Code Notebooks +## Resources for setting up your coding environment + +- [Instructions for setting up Python and the Jupyter Notebook](./ch01/README.md) + +***If you need help with opening the Jupyter notebooks, I made a short [step by step guide](../docs/running_jupyter_nb.pdf) that illustrates this process*** + +- A [quick and great NumPy refresher](https://docs.scipy.org/doc/numpy-dev/user/quickstart.html) that covers everything (and more) you'd need for this book + +- Recommended! To check your coding environment, open the `check_environment.ipynb` (it can be found in this directory) in Jupyter Notebook and execute the code cell: + +![](../images/check_env.png) + + +## Table of contents and code notebooks Simply click on the `ipynb`/`nbviewer` links next to the chapter headlines to view the code examples (currently, the internal document links are only supported by the NbViewer version). **Please note that these are just the code examples accompanying the book, which I uploaded for your convenience; be aware that these notebooks may not be useful without the formulae and descriptive text.** -- [Instructions for setting up Python and the Jupiter Notebook](./ch01/README.md) +
diff --git a/code/bonus/scikit-model-to-json.ipynb b/code/bonus/scikit-model-to-json.ipynb index 36f4ade2..14a7be3c 100644 --- a/code/bonus/scikit-model-to-json.ipynb +++ b/code/bonus/scikit-model-to-json.ipynb @@ -19,9 +19,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -96,9 +94,7 @@ { "cell_type": "code", "execution_count": 3, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -116,7 +112,7 @@ "from sklearn.linear_model import LogisticRegression \n", "from sklearn.datasets import load_iris\n", "import matplotlib.pyplot as plt\n", - "from mlxtend.evaluate import plot_decision_regions\n", + "from mlxtend.plotting import plot_decision_regions\n", "\n", "iris = load_iris()\n", "y, X = iris.target, iris.data[:, [0, 2]] # only use 2 features\n", @@ -151,9 +147,7 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -193,9 +187,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import json\n", @@ -214,9 +206,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -241,9 +231,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -261,9 +249,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "attr_dict = {i: getattr(lr, i) for i in attrs}" @@ -279,9 +265,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", @@ -301,9 +285,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "with open('./sckit-model-to-json/attributes.json', 'w', encoding='utf-8') as outfile: \n", @@ -324,9 +306,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -379,9 +359,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "import codecs\n", @@ -404,9 +382,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -424,7 +400,7 @@ "from sklearn.linear_model import LogisticRegression \n", "from sklearn.datasets import load_iris\n", "import matplotlib.pyplot as plt\n", - "from mlxtend.evaluate import plot_decision_regions\n", + "from mlxtend.plotting import plot_decision_regions\n", "import numpy as np\n", "\n", "iris = load_iris()\n", @@ -462,9 +438,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.0" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/bonus/softmax-regression.ipynb b/code/bonus/softmax-regression.ipynb index fe61160c..9c27d3c5 100644 --- a/code/bonus/softmax-regression.ipynb +++ b/code/bonus/softmax-regression.ipynb @@ -19,9 +19,7 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -152,9 +150,7 @@ { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -191,9 +187,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -242,9 +236,7 @@ { "cell_type": "code", "execution_count": 7, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -284,9 +276,7 @@ { "cell_type": "code", "execution_count": 8, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -320,9 +310,7 @@ { "cell_type": "code", "execution_count": 9, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -368,9 +356,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -405,9 +391,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -428,9 +412,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -513,9 +495,7 @@ { "cell_type": "code", "execution_count": 13, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "# Sebastian Raschka 2016\n", @@ -782,9 +762,7 @@ { "cell_type": "code", "execution_count": 14, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -809,7 +787,7 @@ ], "source": [ "from mlxtend.data import iris_data\n", - "from mlxtend.evaluate import plot_decision_regions\n", + "from mlxtend.plotting import plot_decision_regions\n", "import matplotlib.pyplot as plt\n", "\n", "# Loading Data\n", @@ -844,9 +822,7 @@ { "cell_type": "code", "execution_count": 15, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -896,9 +872,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -923,9 +897,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -953,9 +925,7 @@ { "cell_type": "code", "execution_count": 18, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -980,7 +950,7 @@ ], "source": [ "from mlxtend.data import iris_data\n", - "from mlxtend.evaluate import plot_decision_regions\n", + "from mlxtend.plotting import plot_decision_regions\n", "from mlxtend.classifier import SoftmaxRegression\n", "import matplotlib.pyplot as plt\n", "\n", @@ -1023,9 +993,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.0" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch01/README.md b/code/ch01/README.md index 5404a040..998ee8f2 100644 --- a/code/ch01/README.md +++ b/code/ch01/README.md @@ -58,6 +58,9 @@ After we have successfully installed Python, we can execute pip from the command pip install SomePackage + +(where `SomePackage` is a placeholder for numpy, pandas, matplotlib, scikit-learn, and so forth). + Already installed packages can be updated via the `--upgrade` flag: pip install SomePackage --upgrade @@ -90,7 +93,7 @@ The version numbers of the major Python packages that were used for writing this ## Python/Jupyter Notebook -Some readers weere wondering about the `.ipynb` of the code files -- these files are IPython notebooks. I chose IPython notebooks over plain Python `.py` scripts, because I think that they are just great for data analysis projects! IPython notebooks allow us to have everything in one place: Our code, the results from executing the code, plots of our data, and documentation that supports the handy Markdown and powerful LaTeX syntax! +Some readers were wondering about the `.ipynb` of the code files -- these files are IPython notebooks. I chose IPython notebooks over plain Python `.py` scripts, because I think that they are just great for data analysis projects! IPython notebooks allow us to have everything in one place: Our code, the results from executing the code, plots of our data, and documentation that supports the handy Markdown and powerful LaTeX syntax! ![](./images/ipynb_ex1.png) diff --git a/code/ch01/ch01.ipynb b/code/ch01/ch01.ipynb index 277139f5..ed0c7424 100644 --- a/code/ch01/ch01.ipynb +++ b/code/ch01/ch01.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Copyright (c) 2015, 2016 [Sebastian Raschka](sebastianraschka.com)\n", + "Copyright (c) 2015 - 2017 [Sebastian Raschka](sebastianraschka.com)\n", "\n", "https://github.com/rasbt/python-machine-learning-book\n", "\n", diff --git a/code/ch01/tests/test_notebooks.py b/code/ch01/tests/test_notebooks.py new file mode 100644 index 00000000..b1f6f6cb --- /dev/null +++ b/code/ch01/tests/test_notebooks.py @@ -0,0 +1,28 @@ +import unittest +import os +import subprocess +import tempfile +import watermark +import nbformat + + +def run_ipynb(path): + error_cells = [] + with tempfile.NamedTemporaryFile(suffix=".ipynb") as fout: + args = ["python", "-m", "nbconvert", "--to", + "notebook", "--execute", "--output", + "--ExecutePreprocessor.kernel_name", "python" + fout.name, path] + subprocess.check_output(args) + + +class TestNotebooks(unittest.TestCase): + + def test_appendix_g_tensorflow_basics(self): + this_dir = os.path.dirname(os.path.abspath(__file__)) + run_ipynb(os.path.join(this_dir, + '../appendix_g_tensorflow-basics.ipynb')) + + +if __name__ == '__main__': + unittest.main() diff --git a/code/ch02/ch02.ipynb b/code/ch02/ch02.ipynb index 543562d2..d5b2143d 100644 --- a/code/ch02/ch02.ipynb +++ b/code/ch02/ch02.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Copyright (c) 2015, 2016 [Sebastian Raschka](sebastianraschka.com)\n", + "Copyright (c) 2015-2017 [Sebastian Raschka](sebastianraschka.com)\n", "\n", "https://github.com/rasbt/python-machine-learning-book\n", "\n", @@ -35,29 +35,24 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-03-07 \n", + "last updated: 2017-03-10 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.0.3\n", - "\n", - "numpy 1.10.4\n", - "pandas 0.17.1\n", - "matplotlib 1.5.1\n" + "numpy 1.12.0\n", + "pandas 0.19.2\n", + "matplotlib 2.0.0\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib" + "%watermark -a 'Sebastian Raschka' -u -d -p numpy,pandas,matplotlib" ] }, { @@ -101,7 +96,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "collapsed": true }, @@ -119,10 +114,8 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, + "execution_count": 3, + "metadata": {}, "outputs": [ { "data": { @@ -131,7 +124,7 @@ "" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": { "image/png": { "width": 500 @@ -146,10 +139,8 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { @@ -158,7 +149,7 @@ "" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": { "image/png": { "width": 500 @@ -173,10 +164,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { @@ -185,7 +174,7 @@ "" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": { "image/png": { "width": 600 @@ -200,10 +189,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "data": { @@ -212,7 +199,7 @@ "" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": { "image/png": { "width": 600 @@ -242,10 +229,8 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", @@ -266,7 +251,7 @@ " w_ : 1d-array\n", " Weights after fitting.\n", " errors_ : list\n", - " Number of misclassifications in every epoch.\n", + " Number of misclassifications (updates) in each epoch.\n", "\n", " \"\"\"\n", " def __init__(self, eta=0.01, n_iter=10):\n", @@ -315,7 +300,28 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "**Additional Note**\n", + "### Additional Note (1)\n", + "\n", + "Please note that the learning rate η (eta) only has an effect on the classification outcome if the weights are initialized to non-zero values. If all the weights are initialized to 0, the learning rate parameter eta affects only the scale of the weight vector but not its direction. To have the learning rate influence the classification outcome, the weights need to be initialized to non-zero values. The respective lines in the code that need to be changed to accomplish that are highlighted on below:\n", + "\n", + "```python\n", + " def __init__(self, eta=0.01, n_iter=50, random_seed=1): # add random_seed=1\n", + " ...\n", + " self.random_seed = random_seed # add this line\n", + "\n", + " def fit(self, X, y):\n", + " ...\n", + " # self.w_ = np.zeros(1 + X.shape[1]) ## remove this line\n", + " rgen = np.random.RandomState(self.random_seed) # add this line\n", + " self.w_ = rgen.normal(loc=0.0, scale=0.01, size=1 + X.shape[1]) # add this line\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Additional Note (2)\n", "\n", "I received a note by a reader who asked about the net input function:\n", "\n", @@ -376,9 +382,95 @@ "which is the same as\n", "\n", "```\n", - "| 2 3 | | 4 | | 2*2 + 3*3 | | 13 + bias | | 17 |\n", + "| 2 3 | | 2*2 + 3*3 | | 13 + bias | | 17 |\n", "| 4 5 | x | 2 | + bias = | 4*2 + 5*3 | + bias = | 23 + bias | = | 27 |\n", "| 6 7 | | 3 | | 6*2 + 7*3 | | 33 + bias | | 37 |\n", + "\n", + "```" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Additional Note (3)\n", + "\n", + "For simplicity at this point, we don't talk about shuffling at this point; I wanted to introduce concepts incrementally so that it's not too overwhelming all at once. Since a reader asked me about this, I wanted to add a note about shuffling, which you may want to use if you are using a Perceptron in practice. I borrowed the code from the `AdalineSGD` section below to modify the Perceptron algorithm accordingly (new lines are marked by trailing \"`# new`\" inline comment):\n", + "\n", + "```python\n", + "class Perceptron(object):\n", + " \"\"\"Perceptron classifier.\n", + "\n", + " Parameters\n", + " ------------\n", + " eta : float\n", + " Learning rate (between 0.0 and 1.0)\n", + " n_iter : int\n", + " Passes over the training dataset.\n", + " shuffle : bool (default: True)\n", + " Shuffles training data every epoch if True to prevent cycles.\n", + " random_state : int (default: None)\n", + " Set random state for shuffling and initializing the weights.\n", + "\n", + " Attributes\n", + " -----------\n", + " w_ : 1d-array\n", + " Weights after fitting.\n", + " errors_ : list\n", + " Number of misclassifications in every epoch.\n", + "\n", + " \"\"\"\n", + " def __init__(self, eta=0.01, n_iter=10,\n", + " shuffle=True, random_state=None): # new\n", + " self.eta = eta\n", + " self.n_iter = n_iter\n", + " self.shuffle = shuffle # new\n", + " if random_state: # new\n", + " np.random.seed(random_state) # new\n", + "\n", + " def fit(self, X, y):\n", + " \"\"\"Fit training data.\n", + "\n", + " Parameters\n", + " ----------\n", + " X : {array-like}, shape = [n_samples, n_features]\n", + " Training vectors, where n_samples is the number of samples and\n", + " n_features is the number of features.\n", + " y : array-like, shape = [n_samples]\n", + " Target values.\n", + "\n", + " Returns\n", + " -------\n", + " self : object\n", + "\n", + " \"\"\"\n", + " self.w_ = np.zeros(1 + X.shape[1])\n", + " self.errors_ = []\n", + "\n", + " for _ in range(self.n_iter):\n", + " if self.shuffle: # new\n", + " X, y = self._shuffle(X, y) # new\n", + " errors = 0\n", + " for xi, target in zip(X, y):\n", + " update = self.eta * (target - self.predict(xi))\n", + " self.w_[1:] += update * xi\n", + " self.w_[0] += update\n", + " errors += int(update != 0.0)\n", + " self.errors_.append(errors)\n", + " return self\n", + "\n", + " def _shuffle(self, X, y): # new\n", + " \"\"\"Shuffle training data\"\"\" # new\n", + " r = np.random.permutation(len(y)) # new\n", + " return X[r], y[r] # new\n", + "\n", + " def net_input(self, X):\n", + " \"\"\"Calculate net input\"\"\"\n", + " return np.dot(X, self.w_[1:]) + self.w_[0]\n", + "\n", + " def predict(self, X):\n", + " \"\"\"Return class label after unit step\"\"\"\n", + " return np.where(self.net_input(X) >= 0.0, 1, -1)\n", "```" ] }, @@ -413,10 +505,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "data": { @@ -487,7 +577,7 @@ "149 5.9 3.0 5.1 1.8 Iris-virginica" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -516,10 +606,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { @@ -590,7 +678,7 @@ "149 5.9 3.0 5.1 1.8 Iris-virginica" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -624,16 +712,14 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -684,16 +770,14 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -707,7 +791,7 @@ "\n", "plt.plot(range(1, len(ppn.errors_) + 1), ppn.errors_, marker='o')\n", "plt.xlabel('Epochs')\n", - "plt.ylabel('Number of misclassifications')\n", + "plt.ylabel('Number of updates')\n", "\n", "plt.tight_layout()\n", "# plt.savefig('./perceptron_1.png', dpi=300)\n", @@ -731,10 +815,8 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [], "source": [ "from matplotlib.colors import ListedColormap\n", @@ -762,21 +844,21 @@ " for idx, cl in enumerate(np.unique(y)):\n", " plt.scatter(x=X[y == cl, 0], y=X[y == cl, 1],\n", " alpha=0.8, c=cmap(idx),\n", - " marker=markers[idx], label=cl)" + " edgecolor='black',\n", + " marker=markers[idx], \n", + " label=cl)" ] }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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87dpGFyEz9C5rR++ydvQuk5NkkJoCPJO3/Wy4T0REJJYkg5QneG0REWkB5p5M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\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -794,6 +876,24 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Additional Note (3)\n", + "\n", + "The `plt.scatter` function in the `plot_decision_regions` plot may raise errors if you have matplotlib <= 1.5.0 installed if you use this function to plot more than 4 classes as a reader pointed out: \"[...] if there are four items to be displayed as the RGBA tuple is mis-interpreted as a list of colours\".\n", + "\n", + "```python\n", + "plt.scatter(x=X[y == cl, 0], y=X[y == cl, 1],\n", + " alpha=0.8, c=cmap(idx),\n", + " marker=markers[idx], label=cl)\n", + "```\n", + "\n", + "\n", + "To address this problem in older matplotlib versions, you can replace `c=cmap(idx)` by `c=colors[idx]`." + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -825,10 +925,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { @@ -837,7 +935,7 @@ "" ] }, - "execution_count": 9, + "execution_count": 14, "metadata": { "image/png": { "width": 600 @@ -852,10 +950,8 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { @@ -864,7 +960,7 @@ "" ] }, - "execution_count": 12, + "execution_count": 15, "metadata": { "image/png": { "width": 500 @@ -894,10 +990,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [], "source": [ "class AdalineGD(object):\n", @@ -914,8 +1008,8 @@ " -----------\n", " w_ : 1d-array\n", " Weights after fitting.\n", - " errors_ : list\n", - " Number of misclassifications in every epoch.\n", + " cost_ : list\n", + " Sum-of-squares cost function value in each epoch.\n", "\n", " \"\"\"\n", " def __init__(self, eta=0.01, n_iter=50):\n", @@ -942,7 +1036,14 @@ " self.cost_ = []\n", "\n", " for i in range(self.n_iter):\n", - " output = self.net_input(X)\n", + " net_input = self.net_input(X)\n", + " # Please note that the \"activation\" method has no effect\n", + " # in the code since it is simply an identity function. We\n", + " # could write `output = self.net_input(X)` directly instead.\n", + " # The purpose of the activation is more conceptual, i.e., \n", + " # in the case of logistic regression, we could change it to\n", + " # a sigmoid function to implement a logistic regression classifier.\n", + " output = self.activation(X)\n", " errors = (y - output)\n", " self.w_[1:] += self.eta * X.T.dot(errors)\n", " self.w_[0] += self.eta * errors.sum()\n", @@ -965,16 +1066,14 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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G1ONQVd1fRGaC2wTY2+Q3EvcD1wKh3Vu7At1F5E7cGJ//U9UZUY04iaSnw4QJ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\nXFc8qnDXXfDII1BYCLvtFnRExgTLkhx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ZmTWSZ3LMzMyskVzkmJmZWSO5yDEzM7NGcpFj\nZmZmjeQix8zMzBrpOp15IvPdXehWAAAAAElFTkSuQmCC\n", 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eZ6RXAZU27U87hU/7t6PXqPnc8P4cPurbhrNqV/I6LGOKpNA9OKpqa8OYoPPT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\n7HUs+TOVd3u0tIkn+fB1qQbjJ5MTUxg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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1011,10 +1110,8 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "data": { @@ -1023,7 +1120,7 @@ "" ] }, - "execution_count": 14, + "execution_count": 18, "metadata": { "image/png": { "width": 700 @@ -1046,10 +1143,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [], "source": [ "# standardize features\n", @@ -1060,16 +1155,14 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 20, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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uWNH8RtA+jTzgXmxmNnClXIN6ff1CPsjrzuWEUw3Tp8Oz9yQkHYDFS7KkM3Zs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\nNzML+LGyAUp/HRG397Ld5yQ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SJSUjUvrhm58PhxwCBx7Y/PD54cNreeaZYHvHDti8OShYH3zQcHvVKnjttT37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\nkYz1v0jsUu7ZvpNLAAAAAElFTkSuQmCC\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1125,10 +1218,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [], "source": [ "from numpy.random import seed\n", @@ -1147,8 +1238,9 @@ " -----------\n", " w_ : 1d-array\n", " Weights after fitting.\n", - " errors_ : list\n", - " Number of misclassifications in every epoch.\n", + " cost_ : list\n", + " Sum-of-squares cost function value averaged over all\n", + " training samples in each epoch.\n", " shuffle : bool (default: True)\n", " Shuffles training data every epoch if True to prevent cycles.\n", " random_state : int (default: None)\n", @@ -1236,16 +1328,14 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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JSRpFei5qYtX2ERGnDPXgEfFL4JdD3Y91junH1+hQtCIPKHfs9v306QbuUNSs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\n2ws4GPhu1fxYYCSpu52N8rJ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bNrwM9dEmmt44+gzwaOORC/Yb/TDnfvvZjL25s4FVU6MW1D9Keq7BcpHG6Vun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\nvCTpkibrnVRWnMX2ljRfq+H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QThKpBlSpcEANjV0tbfze//8Iuw+8vgPFtPHV/HLeuUWoyszKTSn04rMR5qia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\nf573+niy/Ctendr9/cAvkuX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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1287,18 +1377,16 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "<__main__.AdalineSGD at 0x10ad57978>" + "<__main__.AdalineSGD at 0x11218fac8>" ] }, - "execution_count": 13, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1328,27 +1416,192 @@ "source": [ "..." ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Appendix" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The code below (not in the book) is a simplified, example implementation of a logistic regression classifier trained via gradient descent. The AdalineGD classifier was used as template and I commented the respective lines that were changed to turn it into a logistic regression classifier (as briefly mentioned in the \"logistic regression\" sections of Chapter 3)." + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "class LogisticRegressionGD(object):\n", + " \"\"\"Logistic regression classifier via gradient descent.\n", + "\n", + " Parameters\n", + " ------------\n", + " eta : float\n", + " Learning rate (between 0.0 and 1.0)\n", + " n_iter : int\n", + " Passes over the training dataset.\n", + "\n", + " Attributes\n", + " -----------\n", + " w_ : 1d-array\n", + " Weights after fitting.\n", + " errors_ : list\n", + " Number of misclassifications in every epoch.\n", + "\n", + " \"\"\"\n", + " def __init__(self, eta=0.01, n_iter=50):\n", + " self.eta = eta\n", + " self.n_iter = n_iter\n", + "\n", + " def fit(self, X, y):\n", + " \"\"\" Fit training data.\n", + "\n", + " Parameters\n", + " ----------\n", + " X : {array-like}, shape = [n_samples, n_features]\n", + " Training vectors, where n_samples is the number of samples and\n", + " n_features is the number of features.\n", + " y : array-like, shape = [n_samples]\n", + " Target values.\n", + "\n", + " Returns\n", + " -------\n", + " self : object\n", + "\n", + " \"\"\"\n", + " self.w_ = np.zeros(1 + X.shape[1])\n", + " self.cost_ = []\n", + " \n", + " for i in range(self.n_iter):\n", + " net_input = self.net_input(X)\n", + " output = self.activation(X)\n", + " errors = (y - output)\n", + " self.w_[1:] += self.eta * X.T.dot(errors)\n", + " self.w_[0] += self.eta * errors.sum()\n", + " \n", + " # note that we compute the logistic `cost` now\n", + " # instead of the sum of squared errors cost\n", + " cost = -y.dot(np.log(output)) - ((1 - y).dot(np.log(1 - output)))\n", + " self.cost_.append(cost)\n", + " return self\n", + "\n", + " def net_input(self, X):\n", + " \"\"\"Calculate net input\"\"\"\n", + " return np.dot(X, self.w_[1:]) + self.w_[0]\n", + "\n", + " def predict(self, X):\n", + " \"\"\"Return class label after unit step\"\"\"\n", + " # We use the more common convention for logistic\n", + " # regression returning class labels 0 and 1\n", + " # instead of -1 and 1. Also, the threshold then\n", + " # changes from 0.0 to 0.5 \n", + " return np.where(self.activation(X) >= 0.5, 1, 0)\n", + " \n", + " # The Content of `activation` changed \n", + " # from linear (Adaline) to sigmoid.\n", + " # Note that this method is now returning the\n", + " # probability of the positive class\n", + " # also \"predict_proba\" in scikit-learn\n", + " def activation(self, X):\n", + " \"\"\" Compute sigmoid activation.\"\"\"\n", + " z = self.net_input(X)\n", + " sigmoid = 1.0 / (1.0 + np.exp(-z))\n", + " return sigmoid" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "from sklearn.datasets import load_iris\n", + "\n", + "iris = load_iris()\n", + "X, y = iris.data[:100, [0, 2]], iris.target[:100]\n", + "\n", + "X_std = np.copy(X)\n", + "X_std[:, 0] = (X[:, 0] - X[:, 0].mean()) / X[:, 0].std()\n", + "X_std[:, 1] = (X[:, 1] - X[:, 1].mean()) / X[:, 1].std()" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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XAGVmv0rx/hfd/aTsmiMieSgFqVJwgqEZnNrawlVj6dhLV5ObbQbNzXm3buipdAX1FuCf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\nrwGXOjKz9wBHApP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HZCru8x8vekPZcl+4+CT+/M/aKpb70p2Vw/uDb51esdx1D26oWO5/nfdnFcv9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\nLCmgREQklhRQIiISSwooERGJpf8P0TDhn+wfB6wAAAAASUVORK5CYII=\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "lr = LogisticRegressionGD(n_iter=25, eta=0.15)\n", + "lr.fit(X_std, y)\n", + "\n", + "plot_decision_regions(X_std, y, classifier=lr)\n", + "plt.title('Logistic Regression - Gradient Descent')\n", + "plt.xlabel('sepal length [standardized]')\n", + "plt.ylabel('sepal width [standardized]')\n", + "plt.legend(loc='upper left')\n", + "plt.tight_layout()\n", + "\n", + "plt.show()\n", + "\n", + "plt.plot(range(1, len(lr.cost_) + 1), lr.cost_, marker='o')\n", + "plt.xlabel('Epochs')\n", + "plt.ylabel('Logistic Cost')\n", + "\n", + "plt.tight_layout()\n", + "# plt.savefig('./adaline_3.png', dpi=300)\n", + "plt.show()" + ] } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch03/ch03.ipynb b/code/ch03/ch03.ipynb index 04dcd12e..8904b9dc 100644 --- a/code/ch03/ch03.ipynb +++ b/code/ch03/ch03.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Copyright (c) 2015, 2016 [Sebastian Raschka](sebastianraschka.com)\n", + "Copyright (c) 2015 - 2017 [Sebastian Raschka](sebastianraschka.com)\n", "\n", "https://github.com/rasbt/python-machine-learning-book\n", "\n", @@ -44,21 +44,18 @@ "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-03-25 \n", + "last updated: 2017-03-10 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.0.3\n", - "\n", - "numpy 1.10.4\n", - "pandas 0.17.1\n", - "matplotlib 1.5.1\n", - "scikit-learn 0.17.1\n" + "numpy 1.12.0\n", + "pandas 0.19.2\n", + "matplotlib 2.0.0\n", + "sklearn 0.18.1\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scikit-learn" + "%watermark -a 'Sebastian Raschka' -u -d -p numpy,pandas,matplotlib,sklearn" ] }, { @@ -121,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "collapsed": true }, @@ -131,6 +128,19 @@ "%matplotlib inline" ] }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Added version check for recent scikit-learn 0.18 checks\n", + "from distutils.version import LooseVersion as Version\n", + "from sklearn import __version__ as sklearn_version" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -196,11 +206,14 @@ "cell_type": "code", "execution_count": 5, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ - "from sklearn.cross_validation import train_test_split\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(\n", " X, y, test_size=0.3, random_state=0)" @@ -377,9 +390,13 @@ " plt.ylim(xx2.min(), xx2.max())\n", "\n", " for idx, cl in enumerate(np.unique(y)):\n", - " plt.scatter(x=X[y == cl, 0], y=X[y == cl, 1],\n", - " alpha=0.8, c=cmap(idx),\n", - " marker=markers[idx], label=cl)\n", + " plt.scatter(x=X[y == cl, 0], \n", + " y=X[y == cl, 1],\n", + " alpha=0.6, \n", + " c=cmap(idx),\n", + " edgecolor='black',\n", + " marker=markers[idx], \n", + " label=cl)\n", "\n", " # highlight test samples\n", " if test_idx:\n", @@ -394,6 +411,7 @@ " X_test[:, 1],\n", " c='',\n", " alpha=1.0,\n", + " edgecolor='black',\n", " linewidths=1,\n", " marker='o',\n", " s=55, label='test set')" @@ -415,9 +433,9 @@ "outputs": [ { "data": { - "image/png": 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a5OuLrW8SiQGQkJ1AC72600LJ3tGeYweOlTg9vJG5EfqG+urlqkwPX5dUdLp3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\nTC+71ceISJpb9t8i0iiCeMa6C9mtdeOKBR4CrnXrHisiA0V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NmsSxQ8eYvGwy9zx1D/0m9ANTmPnaTEL8Qkr74U16dhIRQRFcj7tOr7G9GL14NGcPnK2x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\ngw4YGmqSWI/iam53dzh48FOOHv0UR8c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B2z+BoDCzq/IbElAWFh0axAOXT+GVb51OSJCNm57fyB0vbuZQY7vZpQkh6g4Y\n4dRYDlc+C9e9ZtzfJNxGrkH5iM5uJ0+s2s8jK/cRGKC4Y9FobpmXicMusx4L4TVOpzF3XqrrcsoX\nL8K4pRASbW5dFifXoPxcUGAAd52dw0f/dSbzRsfz4Pt7OOehVbyXXynTJQnhDSUb4emz4ZlzoWaf\n8b3p10k4eZAElI9JjwvlyRtz+fstpxFit/Htv2/iuqfXs7tS7p0SwiMay+GN2+GZxdBUAZc+BrFZ\nZlc1LEgXnw/r7nHyjw3F/OGDAprau7h6djo/ODuHxEiH2aUJ4R/aD8NDk6C7A+beCfPuhuBws6vy\nOYPt4pOA8gP1LZ08/FEBL64vxm4L4OZ5GXzrzGwiHXazSxPC93R3wv6PYewS4/Wm5yHzTIjNNLUs\nXyYBJSiqaeEPHxbw1tZyokPt3LFwNDecPkoGUgjRH04n5L8GH/8aGg7Cd9bJpK5uIoMkBBnxYTxy\nzXTevmseU1Kj+c27uzjr/z7hlbwSmTZJiBPRGgo+gCcWwBu3gSMKrn8DEsebXdmwJy0oP7Z2fw3/\nu2I3W0sPMyoulDsWjeay6SnYbfJ3iRB9mqvh4UkQkQxn/QwmXg4B8n/EnaSLTxyX1poPdx5i2cd7\nyS9rJC02hDsXjebyGakSVGJ40hr2rIB9H8HSPxiLCJZsgORpEBhkdnV+SQJKnJTWmo93V/Gn/+xl\nW+lhUqJDuGPRaK6cmUpQoASVGAa0ht3vwKr/hcptxqwPt/4HwuLNrszvSUCJftFa88meah7+z162\nljQwMsrBzfMyuXp2uiw7L/zXoR3w+m1QtcO4h2nBvTD5KrDJz7w3SECJAdFas3pvDX9ZuY/1hXVE\nOgK54fRRfGNuBokRch+V8AMdTdBYAQljoK0eXvwazLoVJl0pweRlElBi0L4orufJ1Qd4b0cldlsA\nV8xI4db5WWQnyA2Jwgc1HYL1j0PeMxA9Cr612rjOJEwjASWGrLCmhac/PcCrm0rp6nFyzvgR3Dwv\nk9MyY1HyH1xYXdVu+PxR2Poy9HTB+IvgjO8fmdhVmEYCSrhNdVMHL6wr4m+fH6ShtYtxSRF8c24G\nl0xLISRIbvoVFtLTDWiw2WHdX+A/v4KpV8PcuyAu2+zqhIsElHC79q4elm8p4/m1B9lV0UhUiJ2r\nZ6Vx/ZxRpMWGml2eGM5a62DzX2HjM3Dmf8OMG6CjGXo6ITTW7OrElww2oORKoTghh93G12elc1Vu\nGhsK6/j7C+8zAAAYjUlEQVTruiKeXlPIU58eYPH4Edx4egZzs+MICJDuP+ElFVthw1Ow/VXoboeM\n+RAzynhPJnH1OxJQ4pSUUpyWFcdpWXGUN7Tx988P8tKGYj7YeYhRcaFcPSudK2emkhARbHapwh/1\ndBuj7rSG126Bw6Uw9RqYfbvMlefnpItPDEp7Vw/v76jkH+uLWV9YR2CA4pwJI7hmdjrzRsdLq0oM\njdZQ/oUxk/i+/8BdeWAPMVpQ0ekQEmN2hWIApItPeJXDbuOSaSlcMi2F/dXNvLyhmNc2lbIiv5K0\n2JC+VtUIWZtKDET7Ydj+mhFMldsgMAQmXWFcX7KHQPJUsysUXiQtKOE2Hd09vL/jEC9vKGbt/loC\nFMzLSeCKGSmcNzFJlv0Qx9fTDV2t4IiEA5/AC5fAiMmQ+02Y/DVjdnHh02QUn7CUopoWXt9cyhub\nyyhraCMiOJClU5K5YmYquaNi5L4qAYd2wtZ/wLZXjCA67zfGmkyVW42JW+VnxG9IQAlLcjo1nxfW\n8vqmMlbkV9Da2cOouFAun57K5TNSZLj6cLTxGWOIeMVWCAiEnHMh9xbIWWx2ZcJDJKCE5bV0dLMi\nv5LXN5Wy7kAtANPTo7l46kiWTkmWOQD9VXsjFK2BcRcYr1++DhqKYdq1RstJZhP3exJQwqeU1rfy\n1tYK3txazq6KRgIUzMmK4+KpIzl/UjJRoXazSxRD0dUGBe8bS6gXfAA9HfD9rcYSF52tECQt5+HE\ncgGllHoWuBCo0lpP6s9nJKCGp31VTby5pZw3t5ZTVNuK3aY4c0wCF00dydnjR8gyIL6m4H3jfqXO\nJghLhImXweQrIXWWXFcapqwYUAuAZuAFCSjRH1prtpcd5s0t5by9rYLKxnaCAgNYkJPABZOTOHv8\nCKJCpGVlKV1tsP9j2Pmm0YU34RJoKIFVvzOWtciYL0tbCOvdB6W1Xq2UyvDU/oX/UUoxJTWaKanR\n/M8F48k7WM+K/Arey6/ko12HsNsUZ4yO5/xJSZwzIYnYMFme2xTOHtj1phFKBe9DVws4oiFlpvF+\ndBpc8qi5NQq/4NFrUK6AevtkLSil1O3A7QDp6ekzDx486LF6hG9yOjVbSht4L7+SFfkVlNS1YQtQ\nzMmKZcmkZM4ZP4KkKBlg4VGtdVC7H9JmGbM8PDzZaD2NvxDGXwyZC4wZxYU4Dst18UH/Aupo0sUn\nTkVrzY7yRlbkV7BieyUHaloAmJwSxeLxIzhnwgjGJ0fIfVbuUHcA9qwwHgfXGtML3VMAATaoKzSm\nHAqQm6/FqUlAiWFHa83+6mY+3FnFhzsr+aKkAa0hJTqExeMTWTxhBKdlxhEUGGB2qb7B6TQGMSgF\nH/4CPnvY+H7iBBh7PoxdCikzZKCDGDDLXYMSwtOUUoxOjGB0YgTfWZhNdVMHK3dX8eGuQ/wzr4S/\nrjtIRHAgC8YmsGhsImeOSZAZ17+svdGYXmjvB8b1pG+8BYnjjJtnI5JgzBKIzTS7SjFMeXIU30vA\nQiAeOAT8Qmv9zMk+Iy0o4S5tnT18tq+GD3ce4uM9VVQ3dQBGV+CisQksHJfI1NRobMN11vWqXfDu\nvVC8DpzdEBwF2YuMxf9kCQvhZpbs4hsoCSjhCb3XrVYVVLNydxWbi+txaogJtbNgjNG6WjAmwX9H\nBXY0Q+Fqo5U0ai5MuQqaq+Bvl0HOOUZrKXWWDHIQHiNdfEKcgFKKSSlRTEqJ4o5Fo2lo7WT13ho+\n2V3FqoJqlm8pRymYNDKK+TnxzM9JYMaoaIIDfXgAgNMJnz0E+1dC8efg7IKgcIhKMd4PT4TvfGZu\njUKcgrSgxLDmdGq2lR1mdUE1n+6t5oviBrqdmhC7jTlZsczPSWDBmHiyE8KtPTKwoQQOrDTWU5p7\nl/G9R+cYN8lmn2U80udCoJ+2EoWlSRefEG7Q1N7F5wfq+HRvNWv21vQNY0+KdDA/J54zRsdzenac\nNRZiPLAKdr9jBFNNgfG9hHHw3c+NkXZd7WC3QJ1i2JOAEsIDSupaWbOvhjV7a1izr4bDbV0AZCWE\nMTc7jrnZ8czJivP89auOZmNAw8G1cNbPjPuP3rkHtrwIo84wBjhkn2UElJVbemJYkoASwsOcTs3O\nikbW7a9l7f4aNhTW0dLZA8D45EhXYMWRmxHrnjkDqwtg+yvGAIeyTcZoO1sQfGctxOcYszsEhUu3\nnbA8CSghvKyrx8n2ssN9gZVXVE9HtxOlYFxSJLMzYpiVGcvsjFgST9Ul2FYPxeuheC1MvQYSx8OO\nf8NrN8HIGcZUQpkLIO00WapC+BwJKCFM1t7VwxfFDWworGNjUR2bi+tpdbWwRsWFMivDCKtZmbFk\nxIWimirg0z/AwXVQtRPQEGCHS/9iDAXvaoOeTnBEmfsPE2KIJKCEsJiuHic7yxvZWFjLwYJtBJat\nZ2L3DtY7x/FJ6HksSlX8pvh6OpJmEpozn4BRcyE1F+whZpcuhFvJfVBCWIxdaaau+x5TD66FlmoA\nesJiGZ0+nW5bPJ8V1jG25Umc+wOIKA1kZkYwszLKmJ0Zy5TUKN++D0sIN5CAEmKoWuuMQQyleVC6\n0eiS+9pzxki7rjbIPhtGnQ7pc7HF5zBNKaa5PlrW0MbGwjo2FNWxsbCOT/bsASAoMIBpqdFMTzce\n09JiZEkRMexIF58QA9HTBfUHIX608fqf18Out4yvVQAkjIecxXDOrwa1+7qWTvKKjGtYG4vq2Vne\nSGePE4DkKAfT0o4E1uSUKEKCpJUlrE+6+ITwhMYKKPnc1TrKg4otoGzwkxKjhTR6sTHKLnUWjJwO\nweFDOlxsWBDnTkzi3IlJAHR097CzvJEtJQ18UdzAlpIGVuRXAmALUIxLiugLrOnp0WTGhREwXCfA\nFX5HWlBC9OpohvIvoCwP5nwXAoPh/Z/Cuj+DLRhGToOUXGMgw7gLTbv/qKa5g61HBdaWkgaaO7oB\niHQEMi095khLKzWaGH+dBFf4DBnFJ8RglG2CTc9D2WZjqLc2utO4fZURSLX7jfntRkyy7A2xTqex\ncOMXxQ18UVLPF8UNFBxqwun6r50ZH8bUVGOy3MkpUUxMiSI8WDpPhPdIF58QJ9LVDod2QMUXUL7F\n6KY7//fG0hNNlcY1pJHTYdxSo4WUMhPC4ozPxmWbW3s/BAQockZEkDMigqtmpQHQ0tHNttLDfYH1\n+YE6/r2lHDBmQsqMD2OyK7AmpUQxcWQkEQ5ZbkNYiwSU8C9dbUYYhSVAzCgo2QjPLTGmCQIIiTVa\nRriu04xZAj8q9Lv568KCAzk9O47Ts+P6vlfd1EF+2WG2ux4bCutY7gotgKz4sL5W1qSUKCamRBIp\noSVMJF18wrd1NMPWl4xrR+VboHo36B5Y+D+w8L+hrQHWLoPkaUYwRaX5XRgNRU1zB9vLDpNfaoRW\nftlhyg+3972f2Rdaka6WVpR75hkUw4pcgxL+S2toqoDKfKjcBofyja64uXdCZys8kHKkZdQbRKmz\nIWKE2ZX7pJpmo6XV29rKL2ukrKGt7/2U6BDGJ0cyITmCCSMjGZ8cSVpMqIweFCck16CEf+juhJo9\n0N1hjJbTGh6eDIdLjmwTnW4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GlSz9fZ1HWQYySRkORVFYOHpPwQKLRNfU1nL2xRVtPj4+HNh3ACdPJ5Ljkhnx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\nzBLr/wHh17ZBepVDuAAAAABJRU5ErkJggg==\n", 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9yOyyPaitK7fi7OSMrkTX5GKC+ogo1B5U09JokYQQomvpt4YSrYYlv7vRS89f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\nCySazFgSvjcGKJZoDP8dvAuYLXG1GZ8CKoC/jB7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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -657,28 +675,12 @@ "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/Sebastian/miniconda3/lib/python3.5/site-packages/sklearn/utils/validation.py:386: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and willraise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " DeprecationWarning)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([[ 2.05743774e-11, 6.31620264e-02, 9.36837974e-01]])" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "lr.predict_proba(X_test_std[0, :])" + "if Version(sklearn_version) < '0.17':\n", + " lr.predict_proba(X_test_std[0, :])\n", + "else:\n", + " lr.predict_proba(X_test_std[0, :].reshape(1, -1))" ] }, { @@ -732,9 +734,9 @@ "outputs": [ { "data": { - "image/png": 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97D4RqYbNOzdz9YtXc/G8i9lZuDPsOCLl7Kmj3GR3Py82/8Pu3N2PTm20Mlm0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\nRU5ErkJggg==\n", 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RICUEEREBlBBEGsTMOprZ82b2lZkVmNl8Mzve77hEjobmMhI5SsEZ\nWV8BnnXOXRFcNhDoAHzuZ2wiR0MJQeTonQlU1Z510zm3xMd4RBpEp4xEjl4OUOB3ECKNRQlBREQA\nJQSRhlgGDPE7CJHGooQgcvT+CaSa2YQ9C8xsgJmd5mNMIkdNCUHkKDlvquBLgXOCw06XAb8CvvE3\nMpGjo+mvRUQEUAtBRESClBBERARQQhARkSAlBBERAZQQREQkSAlBREQAJQQREQlSQhAREQD+H4I+\nyQPMwNctAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -743,8 +745,8 @@ ], "source": [ "weights, params = [], []\n", - "for c in np.arange(-5, 5):\n", - " lr = LogisticRegression(C=10**c, random_state=0)\n", + "for c in np.arange(-5., 5.):\n", + " lr = LogisticRegression(C=10.**c, random_state=0)\n", " lr.fit(X_train_std, y_train)\n", " weights.append(lr.coef_[1])\n", " params.append(10**c)\n", @@ -861,9 +863,9 @@ "outputs": [ { "data": { - "image/png": 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ELp+7zLejvmXK0in4dPQpc1xVLr2qcvfV9ro+qc+xGwsVOikhxNiqbtamTX3g5ubG5x9/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\ngE0p+5rn7uXh8hjgFwDuvtLM3k9plz4I7C+BV939z2Z2MTA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En4inY4+O5X0STibg6upaY39oPjGBKirYNqjTQZVljugppRxocFBSyqxmsaw5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\nt7mZnW1tLCQZg9oD1O3bx2CS6ZkBVC1ZwuiqKu6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52R5CLBrn0OxjD4p61HnojL0y/8reAyl7D9AV9qCocoru3bnMDKT+yr7PVTzb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\nvwsMkVo+9ggAAAAASUVORK5CYII=\n", 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QAZVy/U2s92OtuUm0tOyVLKrTimuxghtFBH6f54rvMe07dgyzIxHsfksXqYRC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\nE7F0qdctISos7EEREZEvMaC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lpQwKIT4H4DmoMvPHpJRHdbeMDNfSApw5fiH9E8Pb8mSiqbwV9+68MsMWZLfg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\n", 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aAtVxUt6Fv2pkN5rlvymoZelv6N3KcpBOqu6QTspwROafwqn3naS29UkVWFLR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\nA/tkAC385a8Bfwrst8l/vzXwEV6LswewFejsf+dF8eMBpwS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e4dtvdzbp+X/963IuXrzAlClDmTRpBq+++g4ffPAOW7Z8R1FRETffPI/nn3+NvLw8/vSn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\nvkOHuP23v+V/li+n6cgR3jJ+PF985zu5vLq63XG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lHWQ+MUiSEqKU7fljD1Pem8Ki3UsY3GYpkRe+I/F2InbO9iTdcOP2rZPUbFGT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\n", 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SUmjftT1jp4/F1s62Ln8EV5Sbk8u6n9eVPQc1/s7xeLX1apBzi7oNUP8FFgB3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\nVkhOUGZmVkhOUGZmVkhOUGZmVkhOUGZmVkhOUGZ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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1153,16 +1155,16 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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lS/n+++/Zt28fkHpgbdOmDcHBwTRq1EjeY5EpScJ2QJKwuNfFixeZMmUKs2bN\n4ubNmwCUK1eOwYMH06tXL7y8vHSO0D4dPHiQb775hp9++skyqrxGjRqMHDmSjh074uDgoHOEwtZI\nErYDkoTFXf/++y9ffvkl8+fPJzk5GYAmTZoQHBxMy5YtZTRvDrl27RqzZs1ixowZXL2aepO7smXL\n8v7779O7d2+cnZ11jlDYCknCdkCSsPjvv/+YMGEC8+fPx2QyoWkanTp1YuTIkdSsWVPv8PKsW7du\nMW/ePCZOnMh///0HQMmSJRk9ejRBQUE4OTnpHKHQmyRhOyBJOO+6ePEin3zyCXPmzCElJQUHBwd6\n9erFyJEjKV++vN7hiTtSUlL4+eefmTBhAmFhYQCUKVOGcePG0aNHD+mhyMMkCdsBScJ5T1xcHBMn\nTmTKlCkkJiZiMBh49dVXGTNmjIzKtWEmk4mlS5cyfvx4yzXH1atXZ+LEiTRt2lTn6IQeJAnbAUnC\neUdycjKzZs1i/Pjx3LhxA4COHTsyYcIEKlSooHN04mGlpKSwcOFCxowZw4ULFwBo1qwZkyZNomrV\n+yZVE3ZMkrAdkCScN2zZsoUhQ4Zw7NgxAOrVq8ekSZOoWzfDybVELpCYmMi0adP4/PPPiY2NxWAw\n8Oabb/Lxxx/j5+end3giB0gStgOShO3b2bNnee+991i5ciUApUuXZvLkybz88sty/amdiIyMZPz4\n8cycOROTyYSvry8TJkzgjTfekMua7JwkYTsgSdg+JScn89VXXzFu3DgSExNxc3Pjo48+YujQoeTL\nl0/v8IQVHD16lCFDhrB161YAatWqxaxZs2SEux2TJGwHJAnbn927dzNgwACOHDkCQNeuXQkJCaFY\nsWI6RyasTSnFypUrCQ4O5sKFCxgMBgYPHszHH3+Mp6en3uGJbGbvSVjG/YtcJT4+nkGDBvH8889z\n5MgRSpcuzcaNG1m6dKkk4DxC0zQ6duzI8ePHGTp0KABTp06lcuXKbNy4UefohHg00hIWucbWrVvp\n378/Z8+exdHRkeHDhzN69GiZlSePO3DgAAMGDOCvv/4CoF+/fkyePJn8+fPrHJnIDvbeEpYkLGxe\nfHw877//Pt9++y2Qet3o3LlzqV69us6RCVuRkpLClClTGDNmDLdv36Zo0aLMnj2bli1b6h2aeEKS\nhO2AJOHca+/evfTs2ZN///0XJycnRo8ezciRI+V2hiJDYWFh9OvXjz179gAwcOBAJk6ciJubm86R\nicclSdg0lLzwAAAgAElEQVQOSBLOfVJSUvjss8/4+OOPMZlMPPPMMyxatEhu1CAeyGQyERISwujR\no0lOTqZChQr89NNPMoI6l5IkbAckCecuERERdO/enV27dgHw3nvvMWHCBLnsSDySgwcP0rNnT44f\nP46joyOff/457777rtyHOpeRJGwHJAnnHqtXr6ZPnz5ER0dTtGhRFixYwEsvvaR3WCKXSkxMZMSI\nEXzzzTcAtG7dmnnz5uHv769zZOJhSRK2A5KEbV9SUhIjRoxg6tSpgBwsRfa698fdkiVLqF+/vt5h\niYdg70lY+mWE7i5cuMCLL77I1KlTcXR0ZPLkyaxZs0YSsMg27dq149ChQzz//PNcvHiRRo0aMXny\nZOTHudCbtISFrrZt20bXrl25du0axYsXJzQ0lMDAQL3DEnYqOTmZjz76iIkTJwLQpUsX5syZg4eH\nh86RiczYe0tYkrDQhVKKKVOmMGLECEwmE02aNGHJkiXS+hU5YtWqVfTu3Ruj0UjFihVZtWoVTz/9\ntN5hiQzYexKW7miR427dukVQUBDDhg3DZDLxwQcfsHHjRknAIsd06NCBffv2UbFiRcLCwggMDJRb\nXgpdSEtY5KjLly/Tvn179u3bh7u7OwsWLOCVV17ROyyRR8XHx9O7d29WrlyJwWAgJCSE4OBgmQLT\nhkhLWIhs8vfff1O7dm327dtHQEAAu3btkgQsdOXh4UFoaChjxozBbDbz7rvv0r9/f27fvq13aCKP\nkJawyBG//PIL3bt3JzExkXr16rFy5UqeeuopvcMSwuLnn3+mT58+JCYm0rBhQ1auXImPj4/eYeV5\n0hIW4gl98803dOjQgcTERPr06cOWLVskAQub06VLF3bs2EGhQoXYtm0bL7zwAmfPntU7LGHnJAkL\nq7nbvTd48GCUUnz88cf8+OOPODs76x2aEBl69tln2bt3L5UrVyYsLIy6detapkgUwhqkO1pYxe3b\ntwkKCiI0NBQnJyd+/PFHevbsqXdYQjyU2NhYOnbsyJYtW3Bzc2PFihW0aNFC77DyJOmOFuIRGY1G\nWrduTWhoKF5eXmzatEkSsMhVvL29Wb9+Pb169SIhIYG2bduyePFivcMSdshmk7CmaS00TTuhadop\nTdNGZLDdS9O01ZqmHdI07YimaX10CFPc4/r16zRq1IgtW7ZQsGBB/vjjDxo1aqR3WEI8MmdnZ+bN\nm8fw4cNJSUnh1VdfZdq0aXqHJeyMTXZHa5pmAE4BjYFLwH6gm1LqRJoyHwBeSqkPNE3zB04CBZVS\nKRnUJ93ROSAiIoKmTZty6tQpypQpw+bNmyldurTeYQnxxEJCQhg+fDgAH374IZ988olcS5xDpDta\nH3WA00qpc0qpZGAp8PI9ZRTgeef/nkBkRglY5Izw8HDq16/PqVOnqF69On/++ackYGE3hg0bxvz5\n83FwcODTTz/l3XfflckfRLaw1SRcFDif5vGFO+vSmg5U0jTtEnAYGJJDsYl7hIWFUb9+fSIiInju\nuef4/fffKVSokN5hCZGtevXqxfLly3FycmLq1Km89dZbmM1mvcMSuZytJuGH0Rw4qJQqAtQAZmia\nJlOh5LDDhw/ToEEDLl++TMOGDdm8eTP58+fXOywhrKJ9+/asXr2afPnyMWvWLPr06UNKinTAicfn\nqHcAmbgIlEjzuNiddWn1BT4HUEqFa5r2H1AByPCivnHjxln+37BhQxo2bJh90eZRBw8epHHjxkRH\nR9OiRQtWrlyJq6ur3mEJYVUtWrRg/fr1tG3bloULF5KcnMzChQtxdLTVw2nusm3bNrZt26Z3GDnG\nVgdmOZA60KoxcBnYB3RXSoWlKTMDuKaUGq9pWkFSk281pVRUBvXJwKxsdujQIRo3bkxUVBTt2rXj\n559/xsXFRe+whMgxu3btokWLFhiNRrp3786CBQskEVuBvQ/MsskkDKmXKAFfk9plPkcp9YWmaQMA\npZT6XtO0wsA8oPCdp3yulFqSSV2ShLPR4cOHeemll4iKiqJt27YsX75c7oIl8qTdu3fTrFkz4uPj\n6dGjBwsWLMDBwUHvsOyKJGE7IEk4+/zzzz+89NJLREZG0qZNG5YvXy4tYJGn7dy5kxYtWhAfH0/P\nnj2ZN2+eJOJsZO9JODcPzBI57OTJkzRp0oTIyEhat24tCVgI4IUXXmDDhg24u7uzaNEi3nzzTbl8\nSTw0ScLioZw9e5YmTZpw/fp1mjVrxooVKyQBC3FHvXr1WL9+Pa6urvzwww9yHbF4aJKExQNdvnyZ\nJk2acOHCBerVq8eqVaskAQtxjxdffJGVK1dariNOe0WGEJmRJCyyFBkZSZMmTQgPD+fZZ59l7dq1\nuLm56R2WEDapRYsWLFmyBIPBwMcff0xISIjeIQkbJwOzRKZu3rxJ48aN2bt3L5UqVWL79u34+/vr\nHZYQNm/BggX07t0bgHnz5ln+Lx6dDMwSeVJycjKdO3dm7969BAQEsHnzZknAQjykXr168fXXXwPQ\nv39/1q1bp3NEwlZJEhb3MZvN9O/fnw0bNuDn58emTZsoWvTeW3cLIbIyePBgPvjgA0wmE507d2bP\nnj16hyRskCRhcZ+RI0eycOFC3NzcWL9+PU8//bTeIQmRK3366af069ePxMREWrduTVhY2IOfJPIU\nOScs0pkxYwaDBg3C0dGRNWvW0KJFC71DEiJXS0lJoUOHDqxdu5aSJUuyZ88eChYsqHdYuYa9nxOW\nJCws1q5dy8svv4zZbGbu3Ln06dNH75CEsAsJCQk0atSIffv2Ubt2bbZt2yZXGTwke0/C0h0tADhw\n4ADdunXDbDYzZswYScBCZCM3NzdWr15NyZIl2b9/P6+++iomk0nvsIQNkJaw4Pz58wQGBnL58mV6\n9uzJggUL0DS7/eEphG7CwsJ4/vnniYmJYejQoUyZMkXvkGyevbeEJQnncfHx8dSrV4/Dhw/ToEED\nNm3aJHfDEsKKfv/9d5o3b05ycjLffvstb775pt4h2TR7T8LSHZ2Hmc1mevXqxeHDhylXrhwrV66U\nBCyElTVq1IjZs2cD8M477+SpCezF/SQJ52Hjxo1j1apVeHt7s2bNGnx9ffUOSYg8oXfv3gwfPpyU\nlBQ6duzImTNn9A5J6MSq3dGapuVTSt26Z52/UuqG1XaacRzSHX2PZcuW0a1bNwwGAxs2bKBZs2Z6\nhyREnmIymXj55ZdZt24dlSpVYvfu3Xh5eekdls2R7ugns1/TtLp3H2ia1hHYZeV9igf4+++/LaOf\np0yZIglYCB04ODiwePFiKlWqxPHjx+nRowdms1nvsEQOs3ZL+BngR2AbUATwA15TSl2w2k4zjkNa\nwndcv36dWrVqERERQf/+/Zk9e7aMhBZCR+Hh4dSpU4eoqCjGjh0rUyDew95bwlYfHa1pWntgIWAE\nXlRK/WvVHWYcgyRhUu/c06JFC7Zs2UJgYCDbt2+XgVhC2IBff/2VFi1aYDabWb16NW3bttU7JJth\n70nYqt3RmqbNAYKBqkBfYK2maQOtuU+RuVGjRrFlyxYKFCjA8uXLJQELYSOaNm3Kp59+CkDPnj05\nffq0zhGJnGLtc8JHgEZKqf+UUpuAQKCmlfcpMhAaGsqkSZNwcHAgNDSUYsWK6R2SECKNESNG8Mor\nrxAXF0eHDh2Ij4/XOySRA3KiO9oVKKGUOmnVHWUdQ57ujj5x4gS1atXi5s2bTJ06lSFDhugdkhAi\nA0ajkTp16nDixAm6devG4sWL8/yYDemOfgKaprUFDgEb7zyurmnaamvuU6SXkJBAp06duHnzJt27\nd2fw4MF6hySEyISnpyerVq3Cw8ODpUuXMmvWLL1DElZm7e7ocUAdIAZAKXUIKG3lfYo0Bg4cyLFj\nx6hQoQLff/99nv9VLYStu/tdBRgyZAgHDhzQOSJhTdZOwslKqdh71smFcDlk7ty5zJs3D1dXV0JD\nQ/Hw8NA7JCHEQ+jevTtvvfUWSUlJdO7cmZiYGL1DElZi7SR8TNO0HoCDpmnlNE37BrlZR444cuQI\nAwemDkSfOXMmVapU0TkiIcSjmDJlCjVr1uTMmTP069ePvDyuxZ5ZOwm/A1QGbgNLgDhSL1kSVpSQ\nkEDXrl1JTEykT58+MjewELlQvnz5+Pnnn/Hy8mLVqlXMmDFD75CEFchUhnZowIABfP/991SsWJG/\n/voLNzc3vUMSQjym5cuX07lzZ1xcXNi3bx9Vq1bVO6QcZe+jo62ShDVNWwNkWrFSql227zQLeSkJ\n5/UvrBD26I033mD27Nl58oe1vSdha3VHhwCTgf+ARGD2nSUeCLfSPvO8iIgIXn/9dQAmTZokCVgI\nO/HVV19RoUIFwsLCePfdd/UOR2Qja0/g8JdSqtaD1llbXmgJp6Sk8NJLL7Fjxw7atGnD6tWr5XIk\nIezI4cOHqVOnDklJSaxYsYJXXnlF75ByhLSEn4y7pmmW64I1TSsFuFt5n3nSF198wY4dOyhcuDA/\n/vijJGAh7Ey1atWYOHEiAK+99hoXL17UOSKRHazdEm4BfA+cATQgABhw5z7SOcbeW8J///03devW\nJSUlhc2bN9O0aVO9QxJCWIFSilatWrFx40aaN2/Ohg0b7P4Ht723hHPi3tEuQIU7D08opW5bdYcZ\nx2C3STgxMZFnn32WsLAw3nnnHaZNm6Z3SEIIK7p06RLPPPMMUVFRzJgxg7ffflvvkKxKkvCT7kDT\nngdKAo531ymlFlh1p/fHYLdJeOjQoUydOpWnn36aAwcO5KlRk0LkVaGhoXTp0gVXV1cOHz5MuXLl\n9A7JaiQJP0nlmrYQKEPqJA6mO6uVUuqBswjc6cqeSup56zlKqS8zKNMQ+ApwAq4rpRplUpddJuGt\nW7fSuHFjHBwc2L17N7Vr19Y7JCFEDunZsyc//fQTgYGB/Pnnnzg6Oj74SbmQJOEnqVzTwoBKj5oB\nNU0zAKeAxsAlYD/QTSl1Ik0Zb1JvgdlMKXVR0zR/pdSNTOqzuyQcGxvLM888w/nz5xk3bhxjx47V\nOyQhRA6KiYnhmWee4cKFC0yYMIEPP/xQ75Cswt6TsLVHRx8FCj3G8+oAp5VS55RSycBS4OV7yvQA\nViilLgJkloDt1fDhwzl//jy1atVi1KhReocjhMhh+fPnZ+7cuQCMHz+eo0eP6hyReBzWTsL+wHFN\n0zZpmrb67vIQzysKnE/z+MKddWmVB3w1Tftd07T9mqYFZVPMNu+3335j9uzZODs7M2/ePJycnPQO\nSQihgyZNmjBgwACSk5Pp06cPKSkpeockHpG1TyKMs2LdjkBN4CVSrz3erWnabqXUvxkGMu5/oTRs\n2JCGDRtaMTTrMRqNvPbaawCMGTOGypUr6xyREEJPEydOZP369fz999+EhIQwcuRIvUN6Itu2bWPb\ntm16h5FjbHICB03T6gLjlFIt7jweSeqAri/TlBkB5FNKjb/z+Adgg1JqRQb12c054bfffptvv/2W\nmjVrsmfPHmkFCyHYvHkzzZs3x9nZmUOHDlGxYkW9Q8o2ck74MWiaZtQ0LS6DxahpWtxDVLEfKKtp\nWoCmac5AN+DebuxfgHqapjlomuYGBAJh2ftKbMvvv//Ot99+i5OTE3PnzpUELIQAoFmzZvTv35+k\npCT69u2LyWR68JOETbBKElZKeSqlvDJYPJVSXg/xfBMwCNgMHAOWKqXCNE0boGnaG3fKnAA2Af8A\ne4DvlVLHrfF6bEFiYqJlcoYPP/xQJmcQQqQzefJkihYtyt69e+WmPbmITXZHZzd76I4eNWoUn3/+\nOVWqVOHvv//G2dlZ75CEEDZm7dq1tG3bFnd3d44dO0ZAQIDeIT0xe++OliScCxw5coSaNWtiMpnY\nuXMnzz33nN4hCSFsVJcuXQgNDaV169asWbMm199b2t6TsLUvURJPyGQy8frrr5OSksJbb70lCVgI\nkaWvv/4ab29v1q1bx/Lly/UORzyAVZOwpmnvaJrmY8192LvvvvuOvXv3UqRIET777DO9wxFC2LjC\nhQvz5ZepF5K88847REdH6xyRyIq1W8IFgf2apv2saVoLLbf3i+Swixcv8sEHHwAwffp0vL29dY5I\nCJEbvP7667zwwgtcvXo11183bO9yYhYlDWgG9AVqAT+TOiFDuFV3nD6GXHlO+O65nZdffpn/+7//\n0zscIUQucvz4capXr05ycjK7d++mbt26eof0WOSc8BO6k/2u3FlSAB9guaZpE62979zs119/JTQ0\nFDc3N7ncQAjxyCpVqsSwYcOA1Jv8yLXDtsna54SHaJr2NzAR2Ak8o5R6C3gW6GjNfedmt2/fZtCg\nQUDqrSlLlCihc0RCiNzoww8/pESJEhw8eJDvvvtO73BEBqzdEvYFXlFKNVdKhd6ZEQmllBloY+V9\n51pTpkzh1KlTPP300wwdOlTvcIQQuZS7uztTp04FUhPytWvXdI5I3MvaSbi0Uupc2hWapi0EUErZ\n9S0mH1dERASffPIJADNmzJCbcgghnkj79u1p0aIFsbGxjBgxQu9wxD2snYTTTfGjaZoDqV3RIhND\nhw4lMTGRrl270rhxY73DEULkcpqm8c0331imPt25c6feIYk0rDWBwweaphmBqmknbwCukTrxgsjA\nr7/+ysqVK3F3d2fy5Ml6hyOEsBNly5a1tIIHDRokg7RsiFUvUdI07XOl1AdW28HDx2HzlyilpKRQ\nvXp1jh07xhdffCHdRkKIbJWQkECFChU4f/48s2fPtsxLbuvs/RIlqyRhTdMqKKVOaJpWM6PtSqkD\n2b7TrOOx+SQ8Y8YMBg0aROnSpTl+/DguLi56hySEsDNLly6le/fuFChQgFOnTuWKGwBJEn6cSjXt\ne6XUG5qm/Z7BZqWUeinbd5p1PDadhKOioihXrhxRUVGsXLmSDh066B2SEMIOKaWoX78+O3fuZNiw\nYUyaNEnvkB5IkvDjVqxpBuA5pZTuowBsPQkPHjyYb775hkaNGrFly5ZcP+uJEMJ2/fXXX9SuXRsn\nJyeOHTtGuXLl9A4pS/aehK02OvrOtcDTrVW/vTh+/DgzZ87EYDAwdepUScDioSilUCYTKikJlZyM\nMpux5R+awnbUqlWLvn37kpycbLmjltCPtQdmhQC7gZV6NkVtuSXcsmVLNm7cyJtvvsm3336rdzjC\nipRSmM1mUlJSUpekJFRYGFy4AFeuoN24ATduoMXEcP2TTyzlzXcSrEpOpkLdumjJyZjMKRwuCM9e\nTq376OHDYEj9Ta1pmmUp1bEjytUVs6cnytMTs68vys+Pm4MH4+DqioODAw4ODjg6Olr+dXR0xGCQ\nWU7t2ZUrVyhXrhzx8fH8+uuvNGnSRO+QMmXvLeHUL7eVFsAImIEkIO7O4zhr7jOTOFRGy9ixY1VG\nxo4dK+Wl/COXN5lMKjExUY0cOTLD8m+99ZY6cuTI/5YDB5RZ09TYTD6f95U/ckSZHRxUb++HLH/w\noFLw8PX/848y1qmjRpQrl2H5999/X8XHx6ukpCRlNptt7v2X8vZZHlKnILDXxeqzKNkCW2wJm81m\nnn32WQ4dOsTnn38u043lEkopkpOTuX37drolKSmJlORk/ObPx/XkSVxOncLl7FkMSUkAHN+5E7OX\nFwaDwdLadHBwoFDnzuDsjCpYEJ56CgoUAH9/TEFBGPLlw2AwYDAYLC1bFW+kxk/1OHr9GKXyl2Jp\np6XUKVrHEtv/nUidbatd+Xap3dVHjmCOjkbFxkJ0NERGouLjSQgOxmQyYTKZSElJwWQyoS5fptTz\nz9/3ms0uLhzft8/S0obU1omzszPOzs64uLikWxwcHKz/hxBPLDExkfLly3PhwgUWLlxIz5499Q4p\nQ/beErZ2d/SLGa1XSv1htZ1mHIfNJeFFixYRFBREsWLFOHXqFK6urnqHJO5hMplITEzk1q1bluX2\n7dtoRiPmfPnA0TFdeU3TKNeqFc4REZZ15sKFMZcrh2n2bJzKls2Wbt5tZ7ex49wOhr8wnHyO+Szr\nbybdpMKMCiztuJQXSrzw6BXfugV796LCw1Hh4ZhPnUI7eRKziwuRa9aQnJxMUlISSUlJmEwmHG7c\noOTbb5NYuTKJVaqQUL06t0uVwtHZmXz58qVbXFxcZLyDDZo3bx59+/alRIkSnDx5knz58j34STlM\nkvCTVK5pa9I8zAfUAf5WefwSpVu3bvH0008TERHB3Llz6dOnj94h5Xlms5nExMR0S9KdVqzjjRu4\n/fUX7vv3437wIC7//svlFSsgMBAXFxdLa9DJyQnthx9SK3zmGahUCby8niiuU5GnKO9X/qHKKqXY\nfWE3zxe/vzWb3UwmEymrV+Pyyivp13t5EdukCZfGj0+3XtM0XF1d0y3Ozs6SmHVmMpmoUaMGR44c\nYdKkSTY5UEuScHbuTNOKA1OVUjk6jaGtJeGQkBCGDx/OM888w8GDB6X7TgdJSUkkJCRYllu3bt1X\nRtM0io8bh9fy5ek3ODnB3Lnw6qtWjTEqMYry35RnZ7+dPO3/9GPXc+zaMX478xtv134bJwen7Avw\n5k34+2/46y/Yuxd27YILFzD17En89OnpehCSk5PRkpJQjo6Wbm0HBwdcXV1xc3PD3d0dV1dXGRCm\ng40bN9KyZUvy589PeHg4vr6+eoeUjiTh7NxZ6s/eY0qpSjm2U2wrCUdFRVGmTBliYmLYsGEDLVq0\n0DukPCEpKYmbN29aluTk5P9tVArt1i1cfHxwc3PD1dXV0o2qffYZfP45vPACNGgA9etDrVqQQ6cP\nvt3/LUU8i/ByhZcf6/lKKRovaMzvZ3+n8lOVmfvyXGoXrZ3NUaZx/jykpECpUulWp6SkkBISgvPk\nySTUr09svXrE1q2LOU1Pwd3Wsru7O+7u7ri5uUlSzgFKKZo2bcqWLVt47733CAkJ0TukdCQJP0nl\nmvYNqSPdIPWa5OrAWaVUjo4AsKUkPHz4cEJCQmjSpAmbN2+W7jgrMZlMxMfHW5Z0SRcwmEz4/vMP\n3lu34vLbb2gvv4w2PYPL2uPjwcUltfVrRUopLhkvUdSraLbXu/bUWoI3BXMu5hyH3jxElQJVsnUf\nDy0oCBYt+l9sDg6Y6tYlJjiYmOrV7+uN0DTN0kr29PRM/VEk3xerOHjwIDVr1sTZ2ZlTp04REBCg\nd0gWkoSfpHJN653mYQqpCTjH76BlK0n40qVLlClThlu3bvHXX3/x7LMyq2N2UUpx69YtjEYjRqOR\nxMTEdNsNBkPqwfzaNby+/hqH9evRoqP/V6BuXdi9O4ejTnX02lEGbxjM6ajTnBh4Andn92zfx62U\nW2w/u53mZZtne90PTSk4cQLWr4d162DHjtRW8x9/QP36mEymdL0V9yZlBwcHPDw88PT0xMPDA8d7\nBsaJJ9OjRw+WLFlC//79+eHu2AYbIEn4SXegac5ABVJbxCeVUklW3WHGMdhEEh44cCAzZ87klVde\nYcWKFXqHk+uZzWZu3rxJXFwcRqORlJQUy7a0rSgPDw9cXV1TW1EXL0Lx4qkJoVIleOUVePllqFkz\n3SU4OSXJlESpr0txyXgJP1c/1r+63nLJUU7Yd3EfsbdiaVqmaY7t0yImBn79NfVvkMG4CNO8edx8\n9lmMvr4Z9ma4ubnh6emJl5eXTHiSDU6fPk3FihWB1Dv5lS//cAMCrU2S8JNUrmmtgFlAOKABpYAB\nSqkNVttpxnHonoT/++8/ypcvj8lk4ujRo1SqlKOnxe2GyWTCaDQSFxdHfHw8ZrPZss3R0RFPT088\nPT1xP3MGh6pVM06sCxZAYCA8/fiDnbLTgsML2HdxHx83+hhf15wbFGMym6g9uzbDnh9Gj2d65Nh+\nH8r581CiROr/GzZE9exJUrt2GDUNo9FIQkICab/TLi4ueHp64u3tLd3WT+D111/nhx9+oFu3bixZ\nskTvcABJwk9WuaadANoopf6987gMsE4pVcFqO804Dt2TcJ8+fZg/fz5BQUEsWLBA11hym7uJNzY2\nlvj4+HQH33z58uHl5ZV6zjAhAW3xYpgzBw4fhm3bUgdT2ZDoxGh8XH30DgOAFHMKocdC6Valm+0l\nrdOn4aOPYPXq1OuXAfLlgwEDYOpUyzn/u6cf0k5S7+TkhLe3tyTkxxAREUG5cuVISkri8OHDVK1a\nVe+QJAk/UeWatl8pVTvNYw3Yl3ZdTtA7CYeFhVGlShUMBgMnT56kdOnSusWSW5jNZuLj44mNjSUu\nLi5d4nVzc8PLywsvLy+cnZ1h3z74+mtYsQJu304t5OMD06aBDd0F6JLxEs9+/yxH3zqKn5uf3uFk\n6trNa/z+3+90qdxF/wQWG5v6d12wALZvh/feg3tG7yqlLKclYmNj0yVkFxcXS0KWLuuHM2TIEKZN\nm0a7du345Zdf9A5HkvATVa5p3wIBwM+knhPuDEQAvwEopVZabefp49A1CXfp0oXQ0FAGDBjAd999\np1sctu7u4Kro6Oj7Dqaurq7kz58fLy8vnO4dqTx9OrzzDmgaNG0Kr70G7dqljmq2McM2D6NeiXq0\nr9Be71Ay1f+X/vx46EcaBDRgRqsZVC5QWe+QUv33X+rftEiR+7dFRoKvLwoyTciurq74+Pjg7e0t\n1+Zn4erVq5QuXZqEhAT27NlDYGCgrvFIEn6SyjVtbhablVKqn9V2nj4O3ZLw4cOHqV69Oi4uLoSH\nh1O0aPZegmIPUlJSiImJITo6mtt3W7KktmLy58+Pt7d3aos3M7GxMGUK9O0LJUtaP+CHlJCcgJuT\nm95hPLI5B+YwcstIbiTcYMOrG2hRNhdcyx4YmNptPWQI9OgB+fKhlErXm3J3/ICmaXh5eeHj44O7\nu7v+rX0bNGrUKD7//HOaNm3K5s2bdY1FkrAd0DMJd+rUiRUrVhAcHMxXX32lSwy26G4XYnR0dLru\nZgcHB/Lnz0/+/Pn/dz5PKdiyJfUa09mzrX7N7pO6EHeBYZuHER4dzp7+e3Aw5L5WV3RiNKHHQ3nj\n2Sa35q8AACAASURBVDf0DuXBrl6FqlXh2rXUx089BW++CW+/DYUKAamnN2JjY4mJieHmzZuWpzo5\nOeHj44OPj8/9PSx5WFRUFCVLlsRoNLJr1y6ee+453WKRJPwklWtaKeAdoCRguahPKdXOajvNOA5d\nkvCRI0eoWrUqLi4u/PfffxQuXDjHY7A1JpOJ6OhooqKiLPdmBvDw8MDHxwdPT8//3SUpJQVCQ2Hi\nRDh0KHXdsmXQpYsOkT+chOQESnxVgsjESPI55mNXv13UKFxD77CyzdmYs1y7eS1HL6N6KLdvp342\nvvrqf5+VsmXh1KnU0xRpJCUlWXpe0l725OXlha+vr7SO7/joo4/49NNPadmyJevXr9ctDknCT1K5\nph0G5gBHSJ1XGACl1Har7TTjOHRJwl27duXnn3/mnXfeYdq0aTm+f1ty69YtIiMjiYmJsbR6HR0d\n8fX1JX/+/Pd3N4eGwvvvw9mzqY8LFEg97/vmm+Dvn7PBP6Kxv4/l2PVjTG42mYD8tnPnoezQfml7\n6hStw6j6o/QOJWNKpd4EZMoUaNgQgoOzKJraXX23N+YuFxcXy+cyL587joyMJCAggJs3b7J3717q\n1NHnh5ck4SepXNP2KqUe66y+pmktgKmk3u5yjlLqy0zK1QZ2AV0zG+ilRxI+fvw4VapUwcnJifDw\ncIoVK5aj+7cFSimMRiORkZHpugA9PDzw9fXF09Mz8xbH0qXQvTuUKwfDh6fe8tAGp1lLMafgaEh/\n5yazMmPQ7O+exyaziYk7JzL0uaHpplC0WUrd1woGUgdx+aUfnZ6cnExUVBTR0dGWm74YDAZ8fHzw\n8/PLekyCHRs5ciRffvklbdq0Yc2aNQ9+ghVIEn6SyjWtB1AO2AxYRtwopQ484HkG4BTQGLjE/7d3\n3+FRVekDx79n0iYJKaSHkISEICgKgoqiKCBKk1VARURXRWVVxLKrq7K7FlYRf7prYW24uyCr2GWx\nURQBUVakSBeBhPRAek8mZeb8/riZISFtkkzP+TxPnieZuXPvyyWZd057D+wEZkspf23juG+AWmC5\nKyVhcwm4+fPn89prrzn02s5mMpkoKyujqKjI0uWs0+kIDQ0lPDzcuqUiRiOsWwdTprRZTckVpJak\nMvPDmeyctxM/b9ebie0ohkYDO3J3cFlim9uHu5bGRhgyRKuatmgRXNYyZiklFRUVFBcXU1NTY3k8\nJCSEiIiIXrfvd2FhIQMGDKCmpobdu3czcuRIh8fg6UnY3h/XzwHmAc8Bf2/6smaLjlHAMSllppSy\nAfgAaGsbmfuAT4AC24RrG7/++isffPABPj4+PProo84Ox2EaGxspKCjgyJEj5OXlUV9fj4+PDzEx\nMQwePJh+/fq1TMA1Ndr63matZAsvL5g2zWUTMEBKWAoDQgfwzfFvnB2KU72w7QXGvj2WGz65gezy\nbGeH07HDh6Go6FQhlyuv1LZgbCKEICQkhOTkZAYOHEhISAgA5eXlpKWlkZ6eTmVlJc4Y3nKGyMhI\n5s+fD8DTTz/t5Gg8k72T8PVAspRyrJRyfNPX5Va8Lg5o/tec0/SYhRCiHzBdSvkGWklMl7F48WKk\nlMydO5cEc+k9D9bY2MjJkyc5evQoBQUFGI1G9Ho98fHxnHHGGURERLQcW6uv19b2JidrY3ZvvOG8\n4LugrTfe1TesZtoZ05wQjevw9/HH39ufjw59xFfHvnJ2OB075xzIzISnnoLgYNi4Udum8t57Wx3q\n7+9v+R0ODw9Hp9NRXV1NZmYmaWlprYrIeKqHH34Yf39/1qxZw759+5wdjsexdxI+CITa6dwvA82b\nmS6RiNPT03nvvffw9vZm4cKFzg7HrhoaGsjLy+PIkSMUFRVhMpno06cPAwYMsLQiWoz5mkywapXW\nHXjffdrSkvPPhxGuPXu4zFDGg+sfZPans1s9d/p4cG/08MUP8+uCX3nk4keYN3Kes8PpXEgIPPmk\nNunvL3+BPn1adUs35+vrS2xsLIMHDyY6OhovLy8MBgNZWVmkpqa2mGzoiaKjo7nrrrsAWLJkiZOj\n8Tz2HhPeAgxDG9NtPibc4RIlIcRFwFNSyslNPz+mvezU5CwhxHHzt0AEUA38Tkr5eRvnk08++aTl\n53HjxjFu3Lju/aM6sWDBAl577TWPrhHd0NBAYWEhpaWlljefoKAgIiMjCQjooDjFpk0wYYL2/ZAh\n8OyzMH1625NnXERpbSlDXhtCQXUBOqHjl/m/MDjCNTZ+cAdlhjIKqwsZFD7I2aG0r6gIwsKs3kXL\nZDJRWlpKUVGRZYmTn58fUVFRBAcHe+TyppycHJKTkzEajRw9epSBAwfa7Vpbtmxhy5Ytlp8XLVrk\n0WPC9k7CbVbP72yJkhDCCziCNjHrBLADuFFKebid41cAXzh7YlZBQQGJiYkYDAYOHDjA2Wc7afN0\nO2lsbKSwsJCSkhJL8g0ODiYqKgq9NTOXpdSqWo0dq812dpP9YG9dcyvHS4/z6pRXGR4z3NnhuJUH\n1z+IodHAm9PcsFxrbS38618wb16bM/PNExALCwtbJOPo6OiOZ/67qdtvv50VK1Zw991384YDh5A8\nfWKWy1bMalqi9Aqnlig9J4S4C61F/NZpxy4HvnR2En788cd55plnnDqd3x6MRiNFRUUUFxdbSv91\nKfm6uZqGGvy9/T3uTdXepJQ8sP4BHr/scSIDI50dTtc99xwsXKiVQn3hBbj22jZ7bdpKxv7+/kRH\nR9OnTx8HB20/hw8f5qyzzsLPz4/MzEyio6Mdcl2VhLtzUiEq0TZsaPUUWhINtvlFO47H7km4srKS\nxMRESktL+eGHH7jkkkvsej1HMHe7mSdbgbbGNzo6uv2lGg0N2kSrujptfa8bOZB/gCe2PMHqWatV\nwrUjKSXHSo5xRrhrbBrfrm+/hd//Hg4c0H4eNw5efhmGt90b0tbfS2BgIDExMR6ztGnGjBmsWbOG\nhQsX8uyzzzrkmioJewBHJOEXX3yRhx56iEsuuYQffvjBrteyN/Nayfz8fMs634CAAKKjowkMDGz/\nhZs2wYIF2jIQvR6OHwc3KtXZaGrk/LfO58VJL3J5kjWT+JXueGffO8z9bC7zL5jPX8f/lVC9veZu\n2oDRqNUr/8tftCIfOh3s3g3nntvBS4wUFxdbJisChIaGEh0d7fb1qbdv387o0aMJCQkhKyuL4GD7\nt6c8PQl7XlkfJ6ivr+fFF18EcPt1wbW1taSnp5OdnU19fT2+vr4kJCSQlJTUfgLOzdWqW02YoCXg\nlBT46CNL8Xx34a3zZvOtmxk/YLyzQ/Fox0uPI5H8Y8c/eOlHF9/UxMtLK5V67Ji2Q9NVV7XbEj71\nEi+ioqIsS5uEEJSVlXH06FHy8/MtidkdXXTRRYwdO5by8nKWLVvm7HA8gmoJ28CKFSu4/fbbGTp0\nKPv37z+1AYEbaWhoID8/n7KyMuDUG0lYWFjnXbOzZmm1nv39tRbDQw+55F6+ZnWNdbz444vUNNTw\n9OWqAIEz7Du5j8XfL2b5Ncvp4+tG46Ymk9WzqM3q6urIz8+31Kf29vYmJiam9RI+N7Fu3TqmTp1K\nTEwMGRkZ1lXA6wFPbwmrJNxDUkqGDRvGwYMHefvtt7n11lvtch17kVJSXFxMQUEBJpMJIQTh4eFE\nRkZaX7w+LU2bwPLCC5Do2hsWnKw6yaUrLiW1JBVvnTfH7z9OfEi8s8NSmjQYGygzlLnfRK7Nm2HU\nKOhguKa6upoTJ05gMBgAbfJWv3793G68WErJ8OHDOXDggEPe81QS9gD2TMIbN27kyiuvJCYmhszM\nTLcq9F5dXU1eXh51ddoS7qCgIGJiYuz+ydaZpJSMXzmeguoClk5ZyhXJVzg7JKWZl7e/zNbMray+\noc2FDq7p+HEYOlQbfnn9da3eeTuklJSVlZGfn2/ZKCIsLMxSBMRdmHv/hg8fzp49e+zaovf0JOx+\n/aYu5uWXXwbg3nvvdZsE3NjYSHZ2Nunp6dTV1eHr60tiYiKJiYkdJ+B167SSf25MCMEH133Avrv3\nqQTsgnaf2M3iyxc7O4yuqanRis9kZMDUqXDzzVoBkDYIIejbty+DBg0ivGknp5KSEo4dO+ZWlbdu\nvPFGoqKi2LdvH99959CdaT2Oagn3wJEjRxgyZAh6vZ6srCwiI127C838KfzkyZMYjUaEEERGRhIR\nEdHxOHZxsbZU4513YNIkLRm7wVjW3pN7+fDghyy5QpXac3cltSWE+Yc5O4z2NTZqy5eeeEIr8hEZ\nCe+/f6pCXDsMBgN5eXmWHZsCAwNbb3TiohYtWsRTTz3F1VdfzWeffWa366iWsNKuV155BYCbb77Z\n5RNwXV0dGRkZ5ObmYjQa6dOnD4MGDSIqKqrjBLx6NZx1lpaA9Xpt1xk3+eA2sO9A/rP/P+zO2+3s\nUJQe2Jq5lYSXEli8dTGGRoOzw2mbtzc8/DDs36+tJ66s1LZL7IRerycpKYm4uDi8vLyorq4mNTWV\nwsJCl28V33333fj6+vLFF1+Qmprq7HDclmoJd1NJSQnx8fHU1NRw8OBBhg4datPz24qUkqKiIgoK\nCpBS4uXlRWxsbOczM6WE224Dc/3rsWO1En4pKQ6J21aOFR8juW8yXjr3GW9TWvrTt39iyQ9ab8b9\no+7nlSmvODmiTphMcPAgDBvWpZc1NjZy4sQJysvLAS1Bx8XFufTELXMpy/vuu4+lS5fa5RqqJay0\n6Z///Cc1NTVMnDjRZROwwWDg+PHj5OfnI6UkNDSUQYMGERoa2vlECiFg4EAICNC2Hdy0yWUTsEma\nWLFnBSv2rGj13KDwQSoBu7lnJzzLxt9u5IJ+F/DHS9ygCptO1+UEDNrSpfj4eBITE/Hx8cFgMJCW\nlubSa4sffPBBAJYvX25Z3qh0jWoJd0NDQwPJycnk5OSwdu1apnQwG9IZTm/9ent7ExcXR1BQUNdO\n1NAAOTmQlGSfQG0gpyKH6z66jp9yfyLEL4S0+9MIDwh3dliKHUgpW314lFJiaDTg7+O6rUULKbWK\nclOnakU/OmA0GsnPz6ekpARw7VbxhAkT2LRpE3/729946KGHbH5+1RJWWlmzZg05OTkMGTKESZMm\nOTucFurq6khPT7e0fs0zMbucgAF8fFw6AQNEBkRSUltCbJ9YXr/qddeevKP0SFu9N58d+YzpH053\nQjTdsHattoRp2jS45x6orm73UC8vL/r160dSUhK+vr6WXi1XHCv+/e9/D8A//vEPS81sxXoqCXfD\n66+/DmjLklylOpaUkpKSEtLS0qipqcHb25vExETLhI92NTZqMzrXrnVcsDbk5+3Hf2/4L0cWHGHO\nOXPcsgKR0n3v7n+XRy5+xNlhWGfyZK2gja8vvPmmVn96164OXxIYGEhKSgphYWFIKcnPz7csLXQV\nU6dOJSkpiczMTNavX+/scNyO6o7uIvN2XoGBgeTm5hISEmKT8/ZEY2Mjubm5VFZWAhASEkJsbCze\nne3Xm54ON90EP/4I/fppla9ceGvCfSf3sSN3B/POm+fsUBQX0VYXNWiVt3y8XHSzhP37tb+7gwe1\nWdXr1sEVna9Zr6ysJDc3l8bGRnQ6HbGxsfTt29cBAXfu+eef59FHH+Wqq67iyy+/tOm5VXe00oJ5\nM+ubbrrJJRJwVVUVqampVFZWotPp6N+/P/Hx8Z0n4Pff1z6J//gjxMXBqlUunYAB+vr35bFvHyOj\nLMPZoSguoq0EnFqSSvLSZJbvWY5JuuCEpmHDYOdOuP9+OPNMsHLb06CgIFJSUggODsZkMpGbm0t2\ndrZLdAHPnTsXX19f1q5dS3p6urPDcSsqCXdBdXU1K1euBOCee+5xaixSSk6ePElGRgaNjY0EBASQ\nkpJCaKgV28ItXAhz5kBFBUyfDvv2aWsbXVxCSAJrblhDdKBjNhNX3NPyPcvJqcjhjs/vYP5X850d\nTtv0enjlFdi+Xdv4xErmGdRxcXEIISgvLyc1NdVS7MNZIiMjmTVrFlJK3nrrLafG4m5UEu6C9957\nj4qKCkaPHs25Hewnam8NDQ2kp6dT1FQaLzIy0jKBwyqTJmmF5t98UyvGEe56s4nXHlvLt8e/bfX4\npYmXusdMWMVpFl++mFUzV9E/uD/zRrr40EVAQJdfYi59mZKSgl6vb/F+4MzhRXPD5F//+pdLjVm7\nOjUmbCUpJSNHjmTv3r2888473HzzzTaKrmsqKyvJycnBaDRaPhW3u89vR4qLXTL55lbkcs9X9/DF\n0S9I7pvMofmH0Hu7dje54praGxdubxzZZVRWwr33wuLFnVbdMplM5OfnU1xcDEBwcHDnkzHtRErJ\niBEj2LdvH6tWrWLOnDk2Oa8aE1YA+Omnn9i7dy/h4eFcd911Dr++eWZkZmYmRqPRMmuyWwkYXDIB\ngzbb+YesHwjyDWL++fPxEqrQhtI9bSXg3Xm7mfjuRJdb5tPCn/+slYkdORK+/rrDQ80TtOLj49Hp\ndFRUVJCamkptba2Dgj1FCGFpDZtXkCidU0nYSuYJWXfccQd6B09gMhqNZGZmUlhYCEBUVBQDBgzo\nfPJVaiq42fhMREAEH1//MUfvO8pDFz/kujNcFbf0tx//xuyhs127JfzEE9qQUVGRtqxp0SKtFGYH\nQkJCGDhwoKV7+vjx406pYHXTTTcRFBTEtm3b2L9/v8Ov745Ud7QVSktLiY2Npb6+ntTUVJKTk20Y\nXccMBgNZWVnU19fj5eVF//79rSu88dlncMst2uSrb76xagmEox0pOkJGWQaTUlyr4IniuQyNBny9\nfNEJF29/mEzwzDPw1FNapa1Jk2DNmk5XMJhMJvLy8iwJODw8nJiYGId+6FiwYAGvvfYa9957L6++\n+mqPz6e6oxXef/996urqmDBhgkMTcHl5OWlpadTX16PX6xk4cGDnCdhohL/8RZv1XFEBM2bABRc4\nJuAuqqirYO5ncyk3lDs7FKWX0HvrWyXgktoSRv97NF8d/cpJUbVBp9NaxOvXa0NH8fFWLSHU6XTE\nxcURGxuLEILi4mLS09NpbGx0QNCaefO0yXCrVq3CYHDRXa9ciErCVli+fDmgdUU7gpSSgoICsrOz\nkVISEhJCcnJy57OfS0u1kniLF2t/xP/3f/Dpp+AC65nbckHcBbxw5QtIPL83RnFdr+54le0525n2\n/jTu+dK5Sw9bmTgR9u7VNlGxkhCC8PBwkpKS8Pb2pqamhrS0NIclxOHDhzNy5EjKyspYs2aNQ67p\nzlQS7sS+ffvYvXs3oaGhTJ9u/xq1JpOJ7OxsCgoKAIiJiaF///7Wlcc0GLQ/2PBwbULHI49ouyG5\ngJ25OzlYcLDV4zcNu4lQvRVrmxXFThaOWciLE18k2C/YNYdG+vcHP78uvywgIICBAwfi7+9vGSeu\nqKiwQ4CtmRss5gaM0j41JtyJBx54gKVLl9psfKMjDQ0NZGZmYjAY0Ol0xMfHd33jhV27IDISEhPt\nE2QXFdUUsXDjQv69599cHH8x38/93rUnxSi9VnFNMWH+Ye7z+5maCqGhEBHR4WHm6lrmfYpjYmII\nDw+367+z+Tya9PR0EnvwfqTGhHuxuro63n33XUDbvNqezLukGAwGfHx8SE5O7t7OR+ef7zIJGLQ3\ntpX7VuKt8+bi+ItpMDU4OyRFaVN4QOvEZN4q0+UaK6Wl2paIo0bBgQMdHmouZxsVFQXAyZMnOXHi\nhF3/TX379mXmzJlIKXn77bftdh1PoJJwBz7//HNKSko499xzGTlypN2uU1VVxfHjx2loaMDf39+y\n1KBDNTWdLltwBYMjBvPWb97iwD0HeP7K5/H1srKql6K4gEVbFnFmxJmu1zo2GLS5HunpMHq0NnO6\nA0IIoqKiiI+PRwhBSUkJWVlZmOz4HmJuuKxYscKu13F3qju6A1OmTGH9+vUsXbqU++67zw6Rad02\nubm5gFbtxqrx35wcuPpqmDJFm4TlInIqciiuKWZ4zHBnh6IoNlFSW4LeW0+AT9fLS9pdbS3Mm6dt\nvgKwZAk8+min80Cqq6vJysrCaDSi1+tJTEzEx8f26/FNJhNJSUlkZWWxceNGJkyY0K3zqO7oXio7\nO5sNGzbg6+trs/JrpysqKrIk4PDwcEvVmw7t3Kl1Qe3ZAx99pJW4cxE/5fzEzf+9mUaT45ZDKIo9\nhfmHtUrA9cZ65nw6hx25O5wUVRN/f62y1pIl2s8LF8LmzZ2+LDAwkOTkZHx8fCzDYPao9azT6Zg7\ndy4A//73v21+fk+hknA7Vq5ciZSSGTNmEG7jEo/mHZBOnjwJaBMlzOv6OvTxx3DZZXDihLbr0fbt\n0J1xYzuZeeZMZp01i8o61/lgoCi29uauN3n/4Ptc+K8L+cOGPzg3GCHgsce0jVgWLoTLL7fqZX5+\nfi0qbKWnp9ul1OXcuXMRQrB69WpKS0ttfn5PoJJwG6SUlglZt912m83PnZuba9kBqX///kR0MrsR\n0D7xzpqljQXdeSds2ODU+s9pJWmcrDrZ4jEhBI+PfZy+/q6x0bii2MPcc+fy6CWP4qPzIT644w0W\nHGbGDHj22S69xNvbm6SkJAIDA2lsbCQ9PZ3q6mqbhpWYmMjll19OXV0dn376qU3P7SnUmHAbfv75\nZ8477zyioqLIzc3tvEazlUwmEzk5OVRUVCCEICEhwfoZ0Pn52gSMe+6Bhx922vrf6vpqlvywhBf+\n9wLXn3U978581ylxKIqzHSs+xoDQAW5f37xH70tWWLFiBbfffjvjx49n06ZNXX69GhPuhVY1TXS4\n4YYbbJqAs7KyqKioQKfTkZSU1LVf9OhoOHgQ/vhHpxbg2JW3i8XfL6beWI+3zhujyei0WBTFmQaF\nD2qVgKvqq5j/1XzXmRdx4AC8/36Hh5hrEvTt2xcppeV9ylZmzpyJn58fW7ZsscyBUU5RSfg0RqOR\nDz74AMBmE7LMuyBVVVXh5eVFUlISAd3YzLs7G4Db2tgBY3n8ssfZdvs23p7+Nl46tdWgopgt+X4J\nlfWVeOts8+G9R8rL4aqrYM4ceO45bSOIdggh6NevH+Hh4ZZEbKtdmEJCQpg2bRpSSst7q3KK6o4+\nzaZNmywbNaSmpvZ4faA5AdfU1ODt7c2AAQM6XwOckaEVbHfCxtzNlRvKqaqvIi44zqlxKIq7yCzL\nRO+tJ7pPtLND0bz8MvzhD1oCvuce+Mc/OnxfMdetN2+bGhcXR9++PZ/jsXr1aq699lpGjBjBzz//\n3KXXqu5oJxFCTBZC/CqEOCqEeLSN5+cIIfY1ff0ghDjHFtd97733AK0VbMsE7OPjQ1JSUucJeOtW\nGDECHnyww0+ujrBy30ru/OJO16sWpCguKjE0sVUCllLyxOYnSC1JdXxADz4IH36o1Z5+4w249lqt\n0E87hBBER0dbqmvl5ubaZFbz1KlTCQkJYc+ePRw+fLjH5/MkLpmEhRA64FVgEjAUuFEIMeS0w44D\nl0kphwPPAP/s6XXr6ur45JNPgJ53RbeVgP06K8K+erW2a0pZmVaQw4Hbj7Xl7vPvJiowisp6teRI\nUbrr08Of8vTWpxn6+lCe3Pyk4wO4/nptT/HQUG2f8a+/7vQlUVFRREdrHyZyc3N73DWt1+u59tpr\nAW1rWOUUl0zCwCjgmJQyU0rZAHwAXNP8ACnldimleSPa7UCP+0zXrl1LeXk5I0aM4Mwzz+z2eUwm\nU6su6E63IVy2DK67DurqYP58+OQTsEMVm/YUVhdSXd9yeYKvly8rp68k2C/YYXEoiqcZkzCGW4ff\nSr2xnjKDbcZZu+zSS2HbNm1LRCt3g4uMjLS0iHNycnqciM0Nm1WrVqnetWZcNQnHAdnNfs6h4yR7\nJ7Cupxdt3hXdXacnYKtawG+/DXffrXU///Wv2h+Kg8aDG02NvLrjVc549QyW/LDEIddUlN4kpk8M\nb09/m//d/j8WjV/kvEDOOgvuvbdLL4mKimqRiM07MXXHuHHjiI2N5fjx4+zY4eRqYy7EBabw9YwQ\nYjwwFxjT0XFPPfWU5ftx48Yxbty4Fs+Xl5fzxRdfIIRg9uzZ3YpFSkl2djbV1dXWJ2DQ6kAPG6a1\ngO+6q1vX7q7/Hv4v963T6mIfKDiAlNL1itUrigcYHT+61WNGk5G///h3HrjwAfy8u75nsCNERUUh\npaSwsJCcnBx0Ol231hF7eXkxe/ZsXnrpJVatWsWFF17Y5nFbtmxhy5YtPYzafbjk7GghxEXAU1LK\nyU0/PwZIKeX/nXbcMOBTYLKUMq2D83U6O/qdd97hlltuYezYsd36BTBXwiorK7MsQ+p0ElZz9fXQ\nWZe1HZikiRs/vZEbz76RawZfoxKwojjQW7vf4p3977D1tq3O+9v7+WdtOdP48e0eYi61W1xcjBCi\n28ssd+/ezfnnn090dDS5ubl4WdHjp2ZHO8dOIEUIkSiE8AVmA583P0AIkYCWgH/bUQK21urVqwGY\nNWtWl18rpeTEiROUlZWh0+lITEzsWgIGhyTgusa6VnWddULHh9d9yPQh01UCVhQHuzDuQpZNW+a8\nv73sbJg8WduR7fPP2z1MCEFMTAyhoaFIKcnIyOhWremRI0eSlJREfn4+27dv70nkHsMlk7CU0ggs\nAL4GDgEfSCkPCyHuEkL8rumwx4Ew4HUhxB4hRLcHGaqrq1m/fj0A11xzTSdHt1ZYWEhJSYml5FuH\nnxCrqpw263nJD0t45JtHnHJtRVFaGx4znLMiz2r1+Mq9KymsLrR/AHFx2uzpujqYOVOrUd8OIQRx\ncXEEBwdjMpnIyMigvr6+S5cTQjBjxgzgVMOnt3PJJAwgpVwvpRwspRwkpXyu6bFlUsq3mr6fJ6UM\nl1KOlFKOkFKO6u611q9fj8Fg4KKLLiIurmuTrEtLSykoKAAgPj6ePn36tH9wSQlMmKBtwOCETa4f\nuPABfi3+FUOjweHXVhTFOjtyd3DbZ7cx6B+DWPrTUvvOJNbptImgf/oTGI1wyy3w5pvtHi6EeGUb\nFwAAFJNJREFUoH///gQGBmI0GsnIyKCxi42KmTNnAloSdsXhUEdz2STsSOZPZOZfDmtVVlZaaqHG\nxsYSHNzBUp6CAm2bsR074LvvoGkXJXupaajBJFsm+r7+fdl862b03l3sKlcUxWHC/MOYNHAS5XXl\nfJv+rf27qoWAxYvh+ee1n+fPhw4Kauh0OhISEtDr9dTX15OVlYWpC42K0aNHExMTQ0ZGBnv37u1p\n9G6v1yfh+vp6vvzySwBLN4k1amtryc7WVlFFRER0vOdwbi6MHQv79sEZZ8D330PTtH9bk1Ly8aGP\nGfLqEJbvWW6XayiKYj8pYSmsu2kda25Yw0uTXnLchf/4R3jtNXj9deikToKXlxeJiYl4e3tTU1ND\nTk6O1a1anU7H9Ka1yv/97397HLa76/VJeNOmTVRUVDBs2DBSUlKsek1DQwOZmZmYTCZCQkIslWXa\nlJ0Nl10Gv/4KZ5+tlaXs399G0be2Yu8KZn0yi+yKbD7+5WO7XUdRFPsRQnDNkGtI7pvc6rmPDn1E\nXWOdfS48f75Ws8AKPj4+DBgwAJ1OR0VFBSdPnuz8RU2ad0n3dr0+CZt/CaxtBZuLcTQ2NhIQEEBc\nXFzH3UVBQRAWBuedB1u2aFsS2tHss2czMnYkb171JmvnrLXrtRRFcawNqRv407d/QuIaY6l6vZ6E\nhASEEBQXF1tdZ3rcuHGEhoZy6NAhjhw5YucoXVuvTsJGo5E1a9YA1o0HSynJycnBYDDg4+NDQkIC\nOl0ntzA0VKvVunEjdNRl3Q0maWq1b2mATwC75u3irvPvUtsMKoqHCfQN5J+/+afj53VkZLS7oUyf\nPn2IjY0FIC8vj+rq6jaPa87Hx4ff/OY3gOqS7tVJeNu2bRQWFjJw4EDOOafzTZgKCwupqKiwrAX2\n9ray4FjfvloytrHHNj7G3//391aPq/W+iuKZxiSMYXxS66Iam9M3t6r9bjM//6zt7LZgQburOsLC\nwlrsRWzN0iXVJa3p1Um4+azozhJXeXl5i6VIXS7GYQe/O+93rDqwqlVrWFGU3iOzLJOr3ruKIa8N\n4cODH9p+2U9hIdTWahO25s9vNxHHxMRYli5lZWVhNBo7PO3EiRMJCAhg586dZGVl2TZmN9Jrk7CU\n0tIN0llXtMFgsCxFio6Obr9u6tGj8MADdinGcfpyI9BmUf58189469y+BLiiKN1UVV/FmZFnklOR\nw3PbnmvzvaJHJk3Sqmnp9dpubwsWtNk1bS5W5Ovri8FgIC8vr8MPBAEBAUyZMgXAMizYG/XaJHzo\n0CGysrKIjo5m1Kj263wYjUays7MtM6EjIiLaPvDoURg3DpYuhRdesGmsWzO3MmLZCDYe39jqOZWA\nFaV3Gxo1lB137mDZtGW8PvV1+8wFmThR24vYzw/eeAPuv7/Nw8xLl3Q6HeXl5ZSUlHR4WnOFwrVr\ne+8k0l6bhDds2ADApEmT2p1cJaUkLy+Puro6/Pz86NevX9vd1seOacXPT5zQEnE7v6DdsWzXMsa+\nPZb9+ft58ccXbXZeRVE8h5fOi9+d97s2d2rakbvDNq1jcyIOCIALLmj3MD8/P0vlwZMnT1JTU9PB\nKScC8N1333WrFrUn6LVJ2FwretKkSe0eU1JSQnl5OTqdjvj4+LZ3/EhP1yph5eVpBTm+/BICA20W\n5zVDriE6MJpF4xbx6axPbXZeRVE836GCQ1z13lWU1HbcIrXapEmQlqaVt+xASEiIZaJWdnZ2u6Ut\no6OjGTFiBAaDge+//942MbqZXpmEq6ur2bpV2zrsyiuvbPOY2tpay+Lzfv36tT8R67HHICcHxoyx\nSQI+fQwlpk8M6Q+k88TYJ/D38e/RuRVF6V1OVp3k7xP/TkRAO8No3RETY9Vh0dHR+Pv709DQ0GFF\nLXNDyNww6m16ZRL+7rvvqK+v57zzziMyMrLV8+ZxYCklYWFhhHa0vOhf/4L77oOvvoKONm+wwh+/\n/iMfHfqo1eMq+SqK0h0Tkidwy/DWrdZfi361+6qK5j2IVVVVFBcXt3nc5MmTgVNDhL1Nr0zCzceD\n23Ly5Enq6+vR6/XEdPapLyhIm4zV0eYNVrp68NU8vfVptbOIoih2U1FXwfiV4xm5bCTfZXxnm5P+\n9BP8vXXNAl9fX8v4cH5+fpvjvqNHj6ZPnz788ssvlnr8vUmvTsLmT2DNVVRUUFpaatmyq9OKWDZ0\naeKlbLt9myq2oSiK3WSWZeLv7c+BggPMWT2n53WoS0pg8mR4+GF45ZVWTwcHBxMWFmapOHj6jku+\nvr5MmDAB6J2t4V6XhDMyMjhy5AjBwcFceOGFLZ5raGiwrAeOiYlpPQ5cVWWTNcCHCg4x+d3J/FL4\nS6vnQvQhPT6/oihKe86JPodD8w/x13F/5aVJL+Hn7dezE4aFwd/+pn3/4IOwvPXubTExMfj6+lJX\nV0d+fn6r5829kioJ9wLm/+QJEybg4+NjeVxKSW5uLkajkT59+hAWFtbyhTU1MG0a3HAD1HX/k+Oy\nXcsY/uZwNqRt4InNT3T7PIqiKN3l7+PP42MfZ9bQWa2eyy7vRpfwHXfAyy9r3995J3z4YYunzePD\nAMXFxVRWVrZ43pyEv/nmm3ZnUnuqXpeEzTPwTu+KLi0tpaqqCi8vr9Y7I9XXw3XXwXffwfbt0MYn\nOWuNjh+NTui45/x7WDZtWbfPoyiKYmv5VfmMWDaCrPJulJF84AF45hmtmtatt2qrRprx9/e3bPtq\nbvCYJScnM2jQIMrLy9mxY0eP/g3upleVW2poaODbb78FWk7KamhoaLEcqXkLGaNRWxO3bh1ERGi7\nISUkdDuGYdHDyHgwg35B/bp9DkVRFHvYl7+PBaMWkBDSzfe4P/0JDAYYNqzNfdMjIiKoqKigtraW\n/Px8+vU79T44adIkjh07xoYNG7j44ou7+09wO72qJfzjjz9SWVnJkCFDSExMBE5VxTKZTAQFBRHc\nfJazlHDvvVrXSlAQbNgAZ55p9fX+sukv/Jj9Y6vHVQJWFMUVTRw4kafGPdXq8aKaIutWbQgBTz8N\n11/fztPC0tNYUlLSYttDc+9kb1sv3KuScFtLkyoqKqisrESn07UuS2kwwOHDWuHyL76AkSO7dL0h\nEUP4w9d/UEuOFEVxW42mRib8ZwIT/jOBgwUHe3w+vV5vqcGfm5trmS09btw4fH192blzZ7trij1R\nr0rCp3dFG41GTpw4AWjVXVp0QwP4+8P69fDtt1pJyi666ZybWDVzlVpypCiK2zpSdIScihw2Z2zm\nkuWXUFlX2fmL2tKsMRIZGYmfnx/19fUUFhYCEBgYyJgxY5BSsnnzZluE7hZEb2ilCSGklJLKyko2\nb97MFVdcQUBAALm5uZSWlhIQEEBSUlK3k2VuRS5PbnmSJROWEBnYugKXoiiKOyupLeHxTY+TEJLA\no2Me7foJtmyBhQu10r7h4YBWPjg9PR2AlJQU9Ho9O3bswN/fn7PPPtvyfiyEQErpsS2ZXpWEm6ut\nrSUtLQ0hBAMHDmy/NnQnVuxZwX3r7qO6oZq7zruLN6e9aYuQFUVR3EJ1fTWBvh3UzDeZ4MILYdcu\nuOgibXJrU439vLw8SkpKCAwMZMCAAW02hDw9Cfeq7mgzKaWlGzo8PPxUAj58WFuO1AXRfaKpbqhm\nxpAZPDbmMVuHqiiK4rJqG2oZ/uZwDhcebv8gnQ7WrIHERG2J5/XXQ0MDAFFRUXh5eVFdXd1q7XBv\n0SuTcGVlJTU1NXh5eZ3awOHwYbjkErj6aq0wh5WmDprKrnm7WH3DagaEDrBPwIqiKC5oW/Y2RsWN\n4szITlaNxMVpq0siIrTlnnfcAVLi7e1teQ/Oz8/vlZNYe10SllJa1gSbP4WRm6vtk1laCr6+2lcb\nnvvhOTLKMlo9fl6/8+wZsqIoiku6IvkKVs1c1erxemMbPYqDB8PatVpX9Pvvw88/AxAWFmYpaVlS\nYqN9j91Ir0vCJSUl1NfX4+vrq5WmLC+HqVMhOxtGj4YPPgDvtmuYNBgbeOjrhxwcsaIoiutqaxz3\n2o+u5cZPbySnomXVLC64AD75RFvyeZ7WeNHpdJZKWgUFBS0qafUGvWpiltFo5OjRoxiNRhISEgj2\n84MpU2DzZu1T2rZtlpl7bTE0GthzYg+j40c7MHpFURT3cbz0OGe/fja1jbUE+QZx/IHjRAREdPga\nKSXp6enU1NQQERHRYgtZNTHLgxQWFmI0GgkICCAoKEjbEcnXF6KjtXGKpgRcbihn0ZZFGBoNLV6v\n99arBKwoitKB5L7JHL73MNeeeS2zz57daQIGLdGaE29xcTH1XZwg6856Te1oKaXlPzY2NlbrQgkM\n1LpFsrIgKQmADw9+yP3r76egugBvnTd/vuzPzgxbURTF7SSGJvLJrE9oNLXeEckkTehE6/ZfgF5P\nSEgIVVVV1NXV4dvO3BxP02tawkIIEhISSElJwd/f/9QTPj4wcKDlx+LaYgqqC7g4/mKmDprqhEgV\nRVE8g7euZTtPSskV/7mC3Xm7Wx741VcwYgSxXl4MGjRI66nsJXpNS9iss6Icd513F7F9Ypk+ZLoq\nN6koimJD27K3Ud1QzYjYEaceNJm0TR/278d75kzYtKndybGeqFdNzOLoUW0bwqZE/M/d/2TW0FmE\n6EOcHKGiKErvYGg0oPdu2RiSJ04gRo+GzEytmMdHH1meUxOzPEVODowfD1dcoa0HBn7K/YlF3y1y\ncmCKoii9x+kJGOAP+57nwWcvpSylP8yb54SonMdlk7AQYrIQ4lchxFEhRJsVw4UQS4UQx4QQe4UQ\n53Z4wmnTIC8PvLwgIACAZyc8y9jEru+O5Im2bNni7BDcgrpP1lH3qXPqHmlOVJ7gtZ2v8cqxdxn8\nu3qyRw1xdkgO5ZJJWAihA14FJgFDgRuFEENOO2YKMFBKOQi4C+hw54SV7EMOSoHVq8HPD4CowCiu\nGXKNPf4Jbke9IVhH3SfrqPvUOXWPNLFBseyYt4NL4i9heMxw+gf3d3ZIDuWqo9+jgGNSykwAIcQH\nwDXAr82OuQb4D4CU8ichRIgQIlpKmd/WCW+bAd6j7+amDopxKIqiKI53bsy5fD/3e8rrynvdhFiX\nbAkDcUB2s59zmh7r6JjcNo6xGByQQNwZqsazoiiKKxJCEKoPdXYYDueSs6OFENcCk6SUv2v6+WZg\nlJTy/mbHfAEskVL+r+nnjcAjUsqf2zif6/0jFUVRFKt48uxoV+2OzgUSmv3cv+mx04+J7+QYwLP/\nAxVFURT35ard0TuBFCFEohDCF5gNfH7aMZ8DtwAIIS4CytobD1YURVEUV+SSLWEppVEIsQD4Gu2D\nwr+llIeFEHdpT8u3pJRrhRBThRCpQDUw15kxK4qiKEpXueSYsKIoiqL0Bq7aHd1lNi/u4aE6u09C\niDlCiH1NXz8IIc5xRpzOZs3vU9NxFwghGoQQMx0Znyuw8m9unBBijxDioBBis6NjdAVW/M0FCyE+\nb3pfOiCEuM0JYTqVEOLfQoh8IcT+Do7xzPdvKaXbf6F9mEgFEgEfYC8w5LRjpgBfNX1/IbDd2XG7\n6H26CAhp+n6yuk9t36dmx30LfAnMdHbcrnaPgBDgEBDX9HOEs+N20fu0EG2lB0AEUAx4Ozt2B9+n\nMcC5wP52nvfY929PaQlbintIKRsAc3GP5loU9wBChBDRjg3T6Tq9T1LK7VLK8qYft9PB2msPZs3v\nE8B9wCdAgSODcxHW3KM5wKdSylwAKWWRg2N0BdbcJwmY9+4LAoqllK034vVgUsofgNIODvHY929P\nScI2L+7hoay5T83dCayza0SuqdP7JIToB0yXUr4B9MYlcNb8Lp0BhAkhNgshdgohfuuw6FyHNffp\nVeAsIUQesA94wEGxuROPff92ydnRivMJIcajzTgf4+xYXNTLQPPxvd6YiDvjDYwELgcCgR+FED9K\nKVOdG5bLmQTskVJeLoQYCHwjhBgmpaxydmCK/XlKErZpcQ8PZs19QggxDHgLmCyl7KiLyFNZc5/O\nBz4QWqHbCGCKEKJBSnn6enZPZc09ygGKpJQGwCCE2AoMRxsj7S2suU9zgSUAUso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Bubk5jh07Bm9vb4SFhQkdjQiMChcRhEQiweTJkzF+/HhIJBJ8+OGHuHz5Mpo0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\niDWalsW5qstfHvqS/ov62yZ0eP31KrqzfTuEhdXZlNeSrOHp6UlFRQW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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1230,16 +1232,16 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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5Wh65VHHB0sqStPtpJR6XUjT53ZPqDvQAvIUQs7O95AykF3dgilIe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\nuHs3x69fN3c4iqIoD2XM5b4kIYQH2g/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j+e3N3zi16xSpiansmLeDdd+s49Yxt5Y5ryVthK621VD74PZ07tmZ0DWhrPjP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\n9WlQEPNWrWKGu3uJ8c9culQLUQohRAF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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1275,7 +1277,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": { "collapsed": false }, @@ -1290,7 +1292,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": { "collapsed": false }, @@ -1302,7 +1304,7 @@ "" ] }, - "execution_count": 33, + "execution_count": 32, "metadata": { "image/png": { "width": 600 @@ -1315,6 +1317,70 @@ "Image(filename='./images/03_18.png', width=600) " ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Note**\n", + "\n", + "If you have scikit-learn 0.18 and pydotplus installed (e.g., you can install it via `pip install pydotplus`), you can also show the decision tree directly without creating a separate dot file as shown below. Also note that `sklearn 0.18` offers a few additional options to make the decision tree visually more appealing." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "import pydotplus" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "data": { + "image/png": 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EvM5z5eJSs05VNFB7AiaOm2p+CytXL9fXuXLmtSiXCyEgBISAEAiaBMQFJWg+d1m1FQGG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1ZJGlMBtiY7q/I3N8n510QETbClVEXmnGzBluDWNKbZCraoZzLm+gI7gfrweBob3Czw3gl5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\ncsEqQKvVT1Pc+PXCSJfybHkiEvLZMB17ipRu6KhGD4bq+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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.display import Image\n", + "from IPython.display import display\n", + "\n", + "if Version(sklearn_version) >= '0.18':\n", + " \n", + " try:\n", + " \n", + " import pydotplus\n", + " \n", + " dot_data = export_graphviz(\n", + " tree, \n", + " out_file=None,\n", + " # the parameters below are new in sklearn 0.18\n", + " feature_names=['petal length', 'petal width'], \n", + " class_names=['setosa', 'versicolor', 'virginica'], \n", + " filled=True,\n", + " rounded=True)\n", + "\n", + " graph = pydotplus.graph_from_dot_data(dot_data) \n", + " display(Image(graph.create_png()))\n", + "\n", + " except ImportError:\n", + " print('pydotplus is not installed.')" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1332,16 +1398,16 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 35, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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dg8/e/ozEhIrbJLYkDLmSCgN+EkJYABloS9KllFL92aAoFdiCGQvY88seXnzv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\nw98REWsl/VX2cNwWEb+QdKak/yabT/UreWY2M7O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VCdwfyMzpM5nyzBRmTp9J4P7AYsceTAhl0BN3c/ZwGEveXkz4qVN0vq8V8VHx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\nxgiFEKIoc4ok2mmt/fK936qUOlHeAyu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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1385,7 +1451,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 36, "metadata": { "collapsed": false }, @@ -1397,7 +1463,7 @@ "" ] }, - "execution_count": 35, + "execution_count": 36, "metadata": { "image/png": { "width": 400 @@ -1412,16 +1478,16 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 37, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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rGmtNf7a6oDJJyif/V03ZjWb6bwLqsvR39B5lKWSSqjkySVVOXU1YGkUr2nx8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\nV/z3jvEbbs42s3Vm9ou4/d7sP1cADIp7/hr/O3xoZn81s3b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3fxG4MLBsaOv1xa8z9empdO3TFRc3FwAunbzEL6t/Yf3W9dWOB0iKSSJ8czhP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\nbz+Vh9XRGbvk+xwhxJ+FEH8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G6u955536+aNz5/RliO68Exwdf2HTpvk8+2wv3nhjFHv3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\nLpY8QTnnnIul/wexqnkyc68y9gAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1471,22 +1537,23 @@ } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 2", + "display_name": "Python [default]", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, diff --git a/code/ch03/tree.dot b/code/ch03/tree.dot new file mode 100644 index 00000000..d3de07df --- /dev/null +++ b/code/ch03/tree.dot @@ -0,0 +1,20 @@ +digraph Tree { +node [shape=box] ; +0 [label="petal width <= 0.75\nentropy = 1.5799\nsamples = 105\nvalue = [34, 32, 39]"] ; +1 [label="entropy = 0.0\nsamples = 34\nvalue = [34, 0, 0]"] ; +0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ; +2 [label="petal length <= 4.95\nentropy = 0.993\nsamples = 71\nvalue = [0, 32, 39]"] ; +0 -> 2 [labeldistance=2.5, labelangle=-45, headlabel="False"] ; +3 [label="petal width <= 1.65\nentropy = 0.4306\nsamples = 34\nvalue = [0, 31, 3]"] ; +2 -> 3 ; +4 [label="entropy = 0.0\nsamples = 30\nvalue = [0, 30, 0]"] ; +3 -> 4 ; +5 [label="entropy = 0.8113\nsamples = 4\nvalue = [0, 1, 3]"] ; +3 -> 5 ; +6 [label="petal length <= 5.05\nentropy = 0.1793\nsamples = 37\nvalue = [0, 1, 36]"] ; +2 -> 6 ; +7 [label="entropy = 0.8113\nsamples = 4\nvalue = [0, 1, 3]"] ; +6 -> 7 ; +8 [label="entropy = 0.0\nsamples = 33\nvalue = [0, 0, 33]"] ; +6 -> 8 ; +} \ No newline at end of file diff --git a/code/ch04/ch04.ipynb b/code/ch04/ch04.ipynb index e5160299..a0952211 100644 --- a/code/ch04/ch04.ipynb +++ b/code/ch04/ch04.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Copyright (c) 2015, 2016 [Sebastian Raschka](sebastianraschka.com)\n", + "Copyright (c) 2015-2017 [Sebastian Raschka](sebastianraschka.com)\n", "\n", "https://github.com/rasbt/python-machine-learning-book\n", "\n", @@ -44,21 +44,18 @@ "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-05-18 \n", + "last updated: 2017-03-10 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.0.3\n", - "\n", - "numpy 1.11.0\n", - "pandas 0.18.0\n", - "matplotlib 1.5.1\n", - "scikit-learn 0.17.1\n" + "numpy 1.12.0\n", + "pandas 0.19.2\n", + "matplotlib 2.0.0\n", + "sklearn 0.18.1\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scikit-learn" + "%watermark -a 'Sebastian Raschka' -u -d -p numpy,pandas,matplotlib,sklearn" ] }, { @@ -116,24 +113,27 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "from IPython.display import Image" + "from IPython.display import Image\n", + "%matplotlib inline" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "%matplotlib inline" + "# Added version check for recent scikit-learn 0.18 checks\n", + "from distutils.version import LooseVersion as Version\n", + "from sklearn import __version__ as sklearn_version" ] }, { @@ -145,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { "collapsed": false }, @@ -197,7 +197,7 @@ "2 10.0 11.0 12.0 NaN" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -221,7 +221,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": { "collapsed": false }, @@ -236,7 +236,7 @@ "dtype: int64" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -262,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": { "collapsed": false }, @@ -298,7 +298,7 @@ "0 1.0 2.0 3.0 4.0" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -309,7 +309,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "collapsed": false }, @@ -353,7 +353,7 @@ "2 10.0 11.0" ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -364,7 +364,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "collapsed": false }, @@ -416,7 +416,7 @@ "2 10.0 11.0 12.0 NaN" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -428,7 +428,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "collapsed": false }, @@ -464,7 +464,7 @@ "0 1.0 2.0 3.0 4.0" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -476,7 +476,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "collapsed": false }, @@ -520,7 +520,7 @@ "2 10.0 11.0 12.0 NaN" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -547,7 +547,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "collapsed": false }, @@ -560,7 +560,7 @@ " [ 10. , 11. , 12. , 6. ]])" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -576,7 +576,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "collapsed": false }, @@ -589,7 +589,7 @@ " [ 10., 11., 12., nan]])" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -615,7 +615,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": { "collapsed": false }, @@ -627,7 +627,7 @@ "" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": { "image/png": { "width": 400 @@ -642,7 +642,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "collapsed": false }, @@ -654,7 +654,7 @@ "" ] }, - "execution_count": 15, + "execution_count": 14, "metadata": { "image/png": { "width": 400 @@ -684,7 +684,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": { "collapsed": false }, @@ -736,7 +736,7 @@ "2 blue XL 15.3 class1" ] }, - "execution_count": 16, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -769,7 +769,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": { "collapsed": false }, @@ -821,7 +821,7 @@ "2 blue 3 15.3 class1" ] }, - "execution_count": 17, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -837,7 +837,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -851,7 +851,7 @@ "Name: size, dtype: object" ] }, - "execution_count": 18, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } @@ -878,7 +878,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": { "collapsed": false }, @@ -889,7 +889,7 @@ "{'class1': 0, 'class2': 1}" ] }, - "execution_count": 19, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -903,7 +903,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": { "collapsed": false }, @@ -955,7 +955,7 @@ "2 blue 3 15.3 0" ] }, - "execution_count": 20, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -967,7 +967,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": { "collapsed": false }, @@ -1019,7 +1019,7 @@ "2 blue 3 15.3 class1" ] }, - "execution_count": 21, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -1032,7 +1032,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": { "collapsed": false }, @@ -1043,7 +1043,7 @@ "array([0, 1, 0])" ] }, - "execution_count": 22, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -1058,7 +1058,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "collapsed": false }, @@ -1069,7 +1069,7 @@ "array(['class1', 'class2', 'class1'], dtype=object)" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -1095,7 +1095,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "collapsed": false }, @@ -1108,7 +1108,7 @@ " [0, 3, 15.3]], dtype=object)" ] }, - "execution_count": 24, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1123,7 +1123,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": { "collapsed": false }, @@ -1136,7 +1136,7 @@ " [ 1. , 0. , 0. , 3. , 15.3]])" ] }, - "execution_count": 25, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1150,7 +1150,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": { "collapsed": false }, @@ -1175,25 +1175,25 @@ " 0\n", " 10.1\n", " 1\n", - " 0.0\n", - " 1.0\n", - " 0.0\n", + " 0\n", + " 1\n", + " 0\n", " \n", " \n", " 1\n", " 13.5\n", " 2\n", - " 0.0\n", - " 0.0\n", - " 1.0\n", + " 0\n", + " 0\n", + " 1\n", " \n", " \n", " 2\n", " 15.3\n", " 3\n", - " 1.0\n", - " 0.0\n", - " 0.0\n", + " 1\n", + " 0\n", + " 0\n", " \n", " \n", "\n", @@ -1201,12 +1201,12 @@ ], "text/plain": [ " price size color_blue color_green color_red\n", - "0 10.1 1 0.0 1.0 0.0\n", - "1 13.5 2 0.0 0.0 1.0\n", - "2 15.3 3 1.0 0.0 0.0" + "0 10.1 1 0 1 0\n", + "1 13.5 2 0 0 1\n", + "2 15.3 3 1 0 0" ] }, - "execution_count": 26, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -1232,7 +1232,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "collapsed": false }, @@ -1381,7 +1381,7 @@ "4 4.32 1.04 2.93 735 " ] }, - "execution_count": 27, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -1417,7 +1417,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "collapsed": false }, @@ -1559,7 +1559,7 @@ "4 4.32 1.04 2.93 735 " ] }, - "execution_count": 28, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -1583,13 +1583,16 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "from sklearn.cross_validation import train_test_split\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", "\n", "X, y = df_wine.iloc[:, 1:].values, df_wine.iloc[:, 0].values\n", "\n", @@ -1614,7 +1617,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "collapsed": false }, @@ -1628,7 +1631,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "collapsed": false }, @@ -1650,7 +1653,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": { "collapsed": false }, @@ -1719,7 +1722,7 @@ "5 5 1.46385 1.0" ] }, - "execution_count": 32, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" } @@ -1771,7 +1774,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": { "collapsed": false }, @@ -1783,7 +1786,7 @@ "" ] }, - "execution_count": 33, + "execution_count": 32, "metadata": { "image/png": { "width": 500 @@ -1798,7 +1801,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": { "collapsed": false }, @@ -1810,7 +1813,7 @@ "" ] }, - "execution_count": 34, + "execution_count": 33, "metadata": { "image/png": { "width": 500 @@ -1825,7 +1828,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 34, "metadata": { "collapsed": false }, @@ -1850,7 +1853,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 35, "metadata": { "collapsed": false }, @@ -1858,10 +1861,10 @@ { "data": { "text/plain": [ - "array([-0.38381621, -0.1580848 , -0.70045149])" + "array([-0.38383346, -0.15808134, -0.70036089])" ] }, - "execution_count": 36, + "execution_count": 35, "metadata": {}, "output_type": "execute_result" } @@ -1872,7 +1875,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 36, "metadata": { "collapsed": false }, @@ -1880,18 +1883,18 @@ { "data": { "text/plain": [ - "array([[ 0.28023074, 0. , 0. , -0.02814435, 0. ,\n", - " 0. , 0.71027867, 0. , 0. , 0. ,\n", - " 0. , 0. , 1.23597497],\n", - " [-0.64396786, -0.06877257, -0.05720386, 0. , 0. ,\n", - " 0. , 0. , 0. , 0. , -0.92678323,\n", - " 0.06014983, 0. , -0.37107287],\n", - " [ 0. , 0.06157914, 0. , 0. , 0. ,\n", - " 0. , -0.63545405, 0. , 0. , 0.49780455,\n", - " -0.3584355 , -0.57162628, 0. ]])" + "array([[ 0.28030813, 0. , 0. , -0.02801734, 0. ,\n", + " 0. , 0.71015558, 0. , 0. , 0. ,\n", + " 0. , 0. , 1.23621266],\n", + " [-0.64400768, -0.06879233, -0.05720974, 0. , 0. ,\n", + " 0. , 0. , 0. , 0. , -0.92679949,\n", + " 0.06011963, 0. , -0.37101927],\n", + " [ 0. , 0.06144394, 0. , 0. , 0. ,\n", + " 0. , -0.63694567, 0. , 0. , 0.49850798,\n", + " -0.35806863, -0.57045459, 0. ]])" ] }, - "execution_count": 37, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } @@ -1902,16 +1905,16 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 37, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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00cgA1UycaMQgGrUAJxoxCzONagONaiNm0YRe6PC06fGyG/DEAze7AbPRwony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\nU2joAAAAAElFTkSuQmCC\n", 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hhJlA0EmoqkpNTQ3FxcUUFxdTUlJCcXGxd6WkTqcjKiqqXWsYQBHNIuw7YH9j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\nYq2pRZhr6afsJdGxm7iaHKI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EuW1cPje3OTbt3//W4tV8fLQ0bJMna0Ktf/9mj2plfaUm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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1930,11 +1933,11 @@ " 'gray', 'indigo', 'orange']\n", "\n", "weights, params = [], []\n", - "for c in np.arange(-4, 6):\n", - " lr = LogisticRegression(penalty='l1', C=10**c, random_state=0)\n", + "for c in np.arange(-4., 6.):\n", + " lr = LogisticRegression(penalty='l1', C=10.**c, random_state=0)\n", " lr.fit(X_train_std, y_train)\n", " weights.append(lr.coef_[1])\n", - " params.append(10**c)\n", + " params.append(10.**c)\n", "\n", "weights = np.array(weights)\n", "\n", @@ -1974,17 +1977,21 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 38, "metadata": { - "collapsed": true + "collapsed": false }, "outputs": [], "source": [ "from sklearn.base import clone\n", "from itertools import combinations\n", "import numpy as np\n", - "from sklearn.cross_validation import train_test_split\n", "from sklearn.metrics import accuracy_score\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", + "\n", "\n", "class SBS():\n", " def __init__(self, estimator, k_features, scoring=accuracy_score,\n", @@ -2040,16 +2047,16 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 39, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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WeKyIiEQs7SK1D/Bs0fL6ZF2xacBBZrYRWA6cX8axUYqpHTqmXED55J3yiU8e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\nRCS3VKRERCS3VKRERCS3/j+3Km9DJofhRwAAAABJRU5ErkJggg==\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2081,7 +2088,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 40, "metadata": { "collapsed": false }, @@ -2101,7 +2108,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 41, "metadata": { "collapsed": false }, @@ -2123,7 +2130,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 42, "metadata": { "collapsed": false }, @@ -2160,7 +2167,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 43, "metadata": { "collapsed": false }, @@ -2186,9 +2193,9 @@ }, { "data": { - "image/png": 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oYDXb+0gaD5D7kMss53GLpE1t31RijGYXMrDde2lyt9SDpHUtKwNbkK7cynI4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\nX5IW694C/LXeJhViddvfAF6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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2230,32 +2237,30 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 44, "metadata": { "collapsed": false }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/Sebastian/miniconda3/lib/python3.5/site-packages/sklearn/utils/__init__.py:93: DeprecationWarning: Function transform is deprecated; Support to use estimators as feature selectors will be removed in version 0.19. Use SelectFromModel instead.\n", - " warnings.warn(msg, category=DeprecationWarning)\n" - ] - }, { "data": { "text/plain": [ "(124, 3)" ] }, - "execution_count": 46, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "X_selected = forest.transform(X_train, threshold=0.15)\n", + "if Version(sklearn_version) < '0.18':\n", + " X_selected = forest.transform(X_train, threshold=0.15)\n", + "else:\n", + " from sklearn.feature_selection import SelectFromModel\n", + " sfm = SelectFromModel(forest, threshold=0.15, prefit=True)\n", + " X_selected = sfm.transform(X_train)\n", + "\n", "X_selected.shape" ] }, @@ -2268,7 +2273,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 45, "metadata": { "collapsed": false }, @@ -2316,22 +2321,23 @@ } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 2", + "display_name": "Python [default]", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, diff --git a/code/ch05/ch05.ipynb b/code/ch05/ch05.ipynb index 4b9d0f9b..69d69572 100644 --- a/code/ch05/ch05.ipynb +++ b/code/ch05/ch05.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Copyright (c) 2015, 2016 [Sebastian Raschka](sebastianraschka.com)\n", + "Copyright (c) 2015-2017 [Sebastian Raschka](sebastianraschka.com)\n", "\n", "https://github.com/rasbt/python-machine-learning-book\n", "\n", @@ -35,30 +35,25 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-03-25 \n", + "last updated: 2017-03-10 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.0.3\n", - "\n", - "numpy 1.10.4\n", - "scipy 0.17.0\n", - "matplotlib 1.5.1\n", - "scikit-learn 0.17.1\n" + "numpy 1.12.0\n", + "scipy 0.18.1\n", + "matplotlib 2.0.0\n", + "sklearn 0.18.1\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,scipy,matplotlib,scikit-learn" + "%watermark -a 'Sebastian Raschka' -u -d -p numpy,scipy,matplotlib,sklearn" ] }, { @@ -101,8 +96,8 @@ "- [Using kernel principal component analysis for nonlinear mappings](#Using-kernel-principal-component-analysis-for-nonlinear-mappings)\n", " - [Kernel functions and the kernel trick](#Kernel-functions-and-the-kernel-trick)\n", " - [Implementing a kernel principal component analysis in Python](#Implementing-a-kernel-principal-component-analysis-in-Python)\n", - " - [Example 1 – separating half-moon shapes](#Example-1-–-separating-half-moon-shapes)\n", - " - [Example 2 – separating concentric circles](#Example-2-–-separating-concentric-circles)\n", + " - [Example 1 – separating half-moon shapes](#Example-1:-Separating-half-moon-shapes)\n", + " - [Example 2 – separating concentric circles](#Example-2:-Separating-concentric-circles)\n", " - [Projecting new data points](#Projecting-new-data-points)\n", " - [Kernel principal component analysis in scikit-learn](#Kernel-principal-component-analysis-in-scikit-learn)\n", "- [Summary](#Summary)" @@ -118,24 +113,27 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "from IPython.display import Image" + "from IPython.display import Image\n", + "%matplotlib inline" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "%matplotlib inline" + "# Added version check for recent scikit-learn 0.18 checks\n", + "from distutils.version import LooseVersion as Version\n", + "from sklearn import __version__ as sklearn_version" ] }, { @@ -147,10 +145,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { @@ -159,7 +155,7 @@ "" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": { "image/png": { "width": 400 @@ -174,10 +170,8 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { @@ -316,7 +310,7 @@ "4 4.32 1.04 2.93 735 " ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -354,10 +348,8 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "data": { @@ -496,7 +488,7 @@ "4 4.32 1.04 2.93 735 " ] }, - "execution_count": 5, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -527,13 +519,14 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ - "from sklearn.cross_validation import train_test_split\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", "\n", "X, y = df_wine.iloc[:, 1:].values, df_wine.iloc[:, 0].values\n", "\n", @@ -550,10 +543,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [], "source": [ "from sklearn.preprocessing import StandardScaler\n", @@ -621,10 +612,8 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -633,7 +622,7 @@ "\n", "Eigenvalues \n", "[ 4.8923083 2.46635032 1.42809973 1.01233462 0.84906459 0.60181514\n", - " 0.52251546 0.33051429 0.08414846 0.29595018 0.16831254 0.21432212\n", + " 0.52251546 0.08414846 0.33051429 0.29595018 0.16831254 0.21432212\n", " 0.2399553 ]\n" ] } @@ -674,7 +663,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": { "collapsed": true }, @@ -687,16 +676,14 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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ruKHF5s2bS5x75MiRjBo1ir/+9a+0bNmS3/72tyWO/8tf/sK6desoKCjg1ltv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\n9x/rLKrqCd+Tu//X3X/i7oe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UEiVBPWVmlwCPE3SUAMDdt5az3SagTdx0a/YdBT0XeDBMTs2Bn5tZgbs/ESEu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\ntMau3o/jEAE0mrlIJBYUjst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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -736,7 +723,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": { "collapsed": true }, @@ -758,29 +745,27 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Matrix W:\n", - " [[-0.14669811 0.50417079]\n", - " [ 0.24224554 0.24216889]\n", - " [ 0.02993442 0.28698484]\n", - " [ 0.25519002 -0.06468718]\n", - " [-0.12079772 0.22995385]\n", - " [-0.38934455 0.09363991]\n", - " [-0.42326486 0.01088622]\n", - " [ 0.30634956 0.01870216]\n", - " [-0.30572219 0.03040352]\n", - " [ 0.09869191 0.54527081]\n", - " [-0.30032535 -0.27924322]\n", - " [-0.36821154 -0.174365 ]\n", - " [-0.29259713 0.36315461]]\n" + " [[ 0.14669811 0.50417079]\n", + " [-0.24224554 0.24216889]\n", + " [-0.02993442 0.28698484]\n", + " [-0.25519002 -0.06468718]\n", + " [ 0.12079772 0.22995385]\n", + " [ 0.38934455 0.09363991]\n", + " [ 0.42326486 0.01088622]\n", + " [-0.30634956 0.01870216]\n", + " [ 0.30572219 0.03040352]\n", + " [-0.09869191 0.54527081]\n", + " [ 0.30032535 -0.27924322]\n", + " [ 0.36821154 -0.174365 ]\n", + " [ 0.29259713 0.36315461]]\n" ] } ], @@ -824,16 +809,14 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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JmAX9FjM7lKBgYgOwMMJYREQkhmLR3TcetaRERGqLZkEXEZHEU5ISEZHYUpIS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\n", 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LRHaKyA1Vj++OGmDRpN26p/oHjD9wlaNJF5NTjtVYP1IAB9u+VHcKnP8f7OGboETkAICv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\nIiIiK/1/ZLJsZM4WJjMAAAAASUVORK5CYII=\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -860,18 +843,16 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([-2.59891628, 0.00484089])" + "array([ 2.59891628, 0.00484089])" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -897,10 +878,8 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { @@ -910,7 +889,7 @@ " 0.01635336, 0.01284271, 0.00642076])" ] }, - "execution_count": 15, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -925,16 +904,14 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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IiGZUeZT1fGAt8F+B/cvtH9UZVERENKvKo6xTWp5YAvgfkg6sK6CIiGhelZrDNZIOkrRR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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -951,10 +928,8 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [], "source": [ "pca = PCA(n_components=2)\n", @@ -964,16 +939,14 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -989,7 +962,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 20, "metadata": { "collapsed": true }, @@ -1017,9 +990,13 @@ "\n", " # plot class samples\n", " for idx, cl in enumerate(np.unique(y)):\n", - " plt.scatter(x=X[y == cl, 0], y=X[y == cl, 1],\n", - " alpha=0.8, c=cmap(idx),\n", - " marker=markers[idx], label=cl)" + " plt.scatter(x=X[y == cl, 0], \n", + " y=X[y == cl, 1],\n", + " alpha=0.6, \n", + " c=cmap(idx),\n", + " edgecolor='black',\n", + " marker=markers[idx], \n", + " label=cl)" ] }, { @@ -1031,10 +1008,8 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [], "source": [ "from sklearn.linear_model import LogisticRegression\n", @@ -1045,16 +1020,14 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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r05WNLCdZRpaTY00fhoJfaSmLJvxA2z+vUuoNpVTof4U1APrpGgtROtINOnZN\nhcUGl1QCS2Oj1RS3stL6u7ExO0E0m1lOsoyM65X+Y8o/8dUA/qF7EOQtdk1tZRJ0sj0VFggAjz1m\nHQwYCKQWWHJygIkTgW+/Bf7xD+vviROt027bG0SzmeVw3Yki2VrdJyIrAPSKvAuAAjBbKbU8eM1s\nAEeVUk8ne6zly+eGvy4rG4tBg8Zme7jkIXZXm6VbZZbJBuVYkcFx5EjrIEAAeOedlnLsTH+3bFTN\nZSPL4T45/9iyZRW2bl3V5nVa90mJyFUArgVwvlKqKcl1atEi8/dzkVns3FOTzmNnO2BGtowCUm8f\nFcq+GhqsffCrVwOFhdY5Tbt2mbP/iPvk/Mm4fVIiMh7AbQAqkgUookzZtacm3U/7oamw0PeyNRW2\nerV1XzrZWefOwEUXWYcHlpYCb75pnd1kUvbCdSeKpC2TEpFPARwHINSufI1S6oYE1zKTorTZmUnp\n+LQfmZGVlFhZkVLADTdYmVAqgSX2MMHPPwdWrQKuvNJam3Ly9yGK5Pou6AxSlI5sT7HpCkqxzwm0\n3BfvdipjYmshMlGiIMXPSuRJ2aw2s3ufU7wqxETPGSn2YMBUf7dsVBoSOYVBijwrW2sb2dznFCtZ\nMLLrOVniTW7CIEWUAruyj2QB0I7nZGshchsGKaIgXY1NEwUju54zchq0pKTtaVBT+g6SPzFIEUFv\nY9N4wciO5wz9jrt2Rf+OqfyM7r6D5F+s7iMKSlb1Zld1X7IqRCD7z5lJZR+rAckJrO4jaoOOxqbJ\nqhDteM7Y37GkJPr78TIkVgOSTu45mTeOO+7oj717vVGaVFxcirvv/lz3MHwtG/31MuFkh4XI33Ht\nWmD9emDChOR7yXS9LkSAy4PU3r3VcMN0ZSpEWmW55CA/NDaN9zu+9BKwdCkwapQVgC67rPUUo9df\nFzKbq9ekgnOYGkaUfSICrrvp5YfGppFdKkLrYV27Ahs3AqedBtTXtw5AfnhdSD+uSRG1wS+NTUPV\nejk5QM+ewIoVQO/e1j6twYPbfh28+rqQmfifG5GPRG4efustKzCdcQZQUwOcey6weTPLy8ksDFJE\nPhOq1nvnHeCss4D9+62iiB07rEDFTIlMwv8ciXwmVK33ve8B771nBarQhuG33mImRWZhkLLRggUL\nMHr0aOTn5+Pqq6/WPRzysFRbF0VW6517rnUWVWiKL7ZTPNshkQkYpGzUt29f3HHHHZg2bZruoZCH\npdO6KHZY8P+MAAAMlUlEQVTzcP/+0YEpMkCxHRKZwNX7pNrj/NGj0bB3b/h2YXEx3qyqyupzXHrp\npQCAqqoq7NmzJ6uPTRQSWQwR2boo0dpSKtV66T4mkV08GaRiAxDQOgg17N2LtUVF4dujYq53IogR\nZUtk66JzzslORwg7HpMoXdqClIj8O4BLAAQA1AK4SilVk43Hjg1AQOsglO5jpPvzRE6yo3UR2yGR\nCXQm7w8opYYppb4L4BUAczSOhci17DrWg4cjkgm0ZVJKqcaIm8fDyqgcU1hcHJUdFRYXO/n0RFkT\nKoYIrRfFVumZ8phEmdC6JiUi8wBMBXAQwHnZetzYABS6L5IT60vHjh3D0aNHcezYMTQ3N6OpqQm5\nubno0KGD7c9N/mJH6yK2QyIT2BqkRGQFgF6RdwFQAGYrpZYrpW4HcLuI/BbArwDMzcbzZiMAZSPT\nmjdvHu66665wh/O//vWvmDNnDu688852j4+IyA+M6IIuIiUA/q6UGpLg+2rChJYlq7KysRg0aCy7\noBMRudSWLauwdeuq8O2XX74rbhd0ndV9A5VS24I3LwWwKdn1EyfOtX1MRETkjEGDrGQj5OWX74p7\nnc41qftEpAxWwUQ1gOkax0JERAbSWd03WddzExGRO7Beh4iIjMUgRURExmKQIiIiYzFIERGRsRik\niIjIWAxSRERkLAYpmxw5cgTXXHMN+vfvj65du2LEiBF49dVXdQ+LiMhVfBmkli0D1q+3vj52DFiw\nANi/P7vP0dzcjJNOOglvv/026uvrcffdd+Pyyy/Hzp07s/tEREQe5rkg9e23wJNPAkePWre/+AJ4\n9tnoa3r1AmbMAP75T2DOHGDjRuD446OvOXy45evmZuDIkfTG0blzZ9x5550oKSkBAFx88cU4+eST\nsW7dujR/IyIi//JckOrQAdi0Cfjd74CdO4Hrr299zZgxwB13ANOmWUdj/+EPQF5ey/c3bwamTAFq\naqwANXs28NRT7RtXbW0tPv30U5SXl7fvgYiIfMRzQapjR+C++6wMatIkK9hcfnn0NceOAa+/bn2t\nFLB1a/T3Bw8GrrjCCmLTplnZ2dSpmY+pubkZV155Ja666iqUlZVl/kBERD7juSAFAHV1wMGD1tfr\n1rVM/YU89BBw4ACwejVw773W1F9NTfQ1l18O1NYCGzYAt94KHHdcZmNRSuHKK69EXl4eHn744cwe\nhIjIpzwXpBobrSm+X/wCeO896767746+ZsqUlim+MWOsNaxeEUczhqb4xowBfvUr609sEEvVtGnT\nsG/fPixbtown8hIRpUnr8fF2KCgA5s+3puwAa+qvujr6mhNPjL5dWhp9e8cO66js+fOtDKpjR2DV\nKuAnP0lvLNOnT8fmzZvxxhtv4LhMUzEiIh8z4mTetoiIindqrckn8+7cuRP9+/dHfn5+OIOyTt9d\nhClTprS6nifzEpGfBd/PzTmZ1+tOOukkBAIB3cMgInI1z61JEZkm9rMKP7sQpY5BishGgYC1xy60\nLlpdbd1moCJKDaf7iGyUkwOcd57VimvkSGtLxKRJ1v1E1Dbt/6uIyK0iEhCRHrrHQmSH0lIrQL39\ntvV3bDUpESWmNUiJSD8A4wBUt3UtkVtVV1sZ1DnnWH/HbokgosR0Z1IPArhN8xiIbBMIACtXWlN8\nFRXW3ytXck2KKFXa1qRE5IcAdiml1ou0Ko0n8oScHKvvY2gNqrQ0+jYRJWdrkBKRFQB6Rd4FQAG4\nHcAsWFN9kd9LaPnyueGvy8rGYtCgsdkaJpGtYgMSAxQRsGXLKmzduqrN67R0nBCR7wB4A8BhWMGp\nH4A9AE5XSu2Nc73rOk6kix0niMjPEnWc0PKZTin1v0qp3kqpf1FKnQxgN4DvxgtQbvbzn/8cJ554\nIrp164bBgwdj8eLFuodEROQqpkw8KLQx3ZdNhw8fxuw5s1FxQQUm/ngi3n33XVueZ+bMmdixYwcO\nHjyIl156Cbfffjs++ugjW56LiMiLjAhSwYxqf7Yeb+vWrZh67VRc8MMLMOvOWTh06FDU9+fMm4Ot\nh7fip4/+FKOnj8aM22dg27ZtUdc0NzdjzZo1WLlyJQ4cOJDROE477TTk5+cDsM6VEhFs3749s1+K\niMiHjAhS2bRv3z5cfcPVKP5+MSb8fgI+C3yG38z8TdQ1K99eifE3j0fX4q44ZfQpOOX8U/D++++H\nv3/kyBFc88trcMdDd+CPz/0Rl1xxScbB5cYbb8Txxx+PU089FX369MFFF13Urt+PiMhPPBekPvzw\nQ/Qq74WRF41EUWkRJt46EWvWrsE333wTvqagoAAHvrSyI6UUGmoaUFBQEP7+s88+i/15+3HVY1fh\nJ/f9BKOmjsK8B+ZlNJ4FCxagsbER77zzDiZNmoS8vLz2/YJERD7iuSCVn5+Prw98Ha76O1x/GCKC\njh07hq+57abbsHT2Uqx4YgWem/Mccr/KxQUXXBD+/pe1X6Lf0H7ICdYK9x/WH1/UfJHxmEQEZ599\nNnbt2oXHHnss48chIvIbzzWYPeuss3DCn0/Ac3OeQ+9Te2PTa5tw/VXXIze35Ve9+OKL0bdvX7z/\n/vvodlY3TJw4EZ06dQp/f9iQYfj743/HiPEj0KmwE95f+j6GDxne7rE1NzdzTYqIKA2eC1IdO3bE\n4scW47nnnkPN3hpMvnEyzj///FbXDR8+HMOHxw8848aNw+atm/HIFY8gp0MOhpUPw+z5s9MaR11d\nHd58801MmDABnTp1wooVK7BkyRIsWbIko9+LiMiPeHx8Ek1NTWhqakJhYWHaP7tv3z5MnjwZn3zy\nCQKBAEpLS3HzzTfj6quvjns9N/MSkZ/x+PgM5OXlZVzo0LNnT6xatSq7AyIi8hnPFU4QEZF3MEgR\nEZGxGKSIiMhYDFJERGQsBikiIjIWgxQRERnL1SXoxcWl8MrR88XFpbqHQERkHFcHqbvv/lz3EIiI\nyEac7nPQli2rdA/BFfg6pYavU9v4GqXG5NeJQcpBW7eu0j0EV+DrlBq+Tm3ja5Qak18nBikiIjIW\ngxQRERnLNV3QdY+BiIjsFa8LuiuCFBER+ROn+4iIyFgMUkREZCwGKSIiMhaDlCYicquIBESkh+6x\nmEhEHhCRTSLysYgsFZFC3WMyhYiMF5HNIrJVRH6rezwmEpF+IvKmiGwQkfUi8mvdYzKViOSIyIci\n8pLuscTDIKWBiPQDMA5Ate6xGOx1AOVKqeEAPgUwU/N4jCAiOQAeAfADAOUApojIYL2jMlIzgBlK\nqXIAZwG4ka9TQjcD2Kh7EIkwSOnxIIDbdA/CZEqpN5RSgeDNNQD66RyPQU4H8KlSqlopdRTAEgCX\naB6TcZRSNUqpj4NfNwLYBKCv3lGZJ/iB+SIAT+oeSyIMUg4TkR8C2KWUWq97LC5yNYB/6B6EIfoC\n2BVxezf45puUiPQHMBzA+3pHYqTQB2Zj9yK5ugu6qURkBYBekXfB+o/gdgCzYE31RX7Pl5K8TrOV\nUsuD18wGcFQp9bSGIZLLiUgBgOcB3BzMqChIRC4GUKuU+lhExsLQ9yIGKRsopcbFu19EvgOgP4B/\ninUQVj8A60TkdKXUXgeHaIREr1OIiFwFayrifEcG5A57AJwUcbtf8D6KISK5sALUX5RSL+oej4HG\nAPihiFwEoBOALiLylFJqquZxRWHHCY1EZAeAEUqpA7rHYhoRGQ/gPwBUKKW+0j0eU4hIBwBbAHwf\nwJcAPgAwRSm1SevADCQiTwHYp5SaoXssphORcwHcqpT6oe6xxOKalF4KhqbYBngYQAGAFcHy2Ed1\nD8gESqljAG6CVf24AcASBqjWRGQMgJ8BOF9EPgr+NzRe97gofcykiIjIWMykiIjIWAxSRERkLAYp\nIiIyFoMUEREZi0GKiIiMxSBFRETGYpAicpCIHAvu2VkvIs+ISH7w/l4i8jcR+VREqkTkZREZGOfn\nF4tIrYh84vzoiZzHIEXkrK+VUiOUUkMAHAUwPXj/CwDeVEqdopQaDetokl5xfv7PsI7pIPIF9u4j\n0udtAENE5DwAR5RST4S+kahLvlLqHREpdWqARLoxkyJylgDh5qcXAlgP4DsA1ukcFJGpGKSInNVJ\nRD6E1Rj2cwCL9Q6HyGyc7iNy1mGl1IjIO0RkA4DJmsZDZDRmUkTOatX1Xin1JoDjROSa8EUiQ4Kd\nvBM9Brvnky8wSBE5K9GxA5cBGCci20RkPYB7ANTEXiQiTwN4F0CZiOwUkV/YN1Qi/XhUBxERGYuZ\nFBERGYtBioiIjMUgRURExmKQIiIiYzFIERGRsRikiIjIWAxSRERkrP8P+V5nCCAOqjYAAAAASUVO\nRK5CYII=\n", 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B/qJgwy8JGS1K6zdgfrcGmxkNKBF5DMAtABpU9XKTY+mtyEXDkYH10X8sTbspQRO7TJuc\n7vIykJPZvqenSovHUaS5KAf1lS+sBu5Jsw8Eg0xXUGsB/BzArw2PwzPhgVXXWod+o0JTgum0BivI\nXaZNfxB7GcjJbN+TyCGO6X4cRSbdW0xI5G4N3dYiMZySYTSgVPU1EbnU5Bj8VNynuPui4VHVXVra\nATvXYAW5y7QNH8ReBnIi93MSrbSC/EUhkpebyWZk40WUtUhA5J52DKRUmK6geiQi5QDKAWDM+DGG\nR9N70Xa5aLR0DZaJXaZNfhAD3gdyT/dzEq20TB1HkWq4mK6KfZHQ4liAoeQd6wNKVVcDWA04beaG\nh+OZ4j7FKO5T3Nl00bloOGwNlqn1V8lMU3mltx/EXkwhmTr2oadKy9S4vAgXG6piT0QcQ+HXybEU\nnfUBlS0iFw1XX6jGkIfX4dMz6AysICusINuOe/tB7NUUkolADn/vWI9NjcurcDFdFfdaZOt3lyk7\nBlKQGFCWKu1XitJLQo+j7XLh9xlYQbUd9+aD2OspJFvXAXk5rmSqTS/CJW1Oy40IJCCy9ZtTdqaY\nbjN/AsBiACNF5DCAh1V1jckx2aq4TzGKLwlteht+BpYrnXe5SPaD2I8ppMiFsbEWygbNi18Ukq02\nUw0Xa0/LjXJybKbu1pAJ4gaUiEwDUAzgbVVtCnt+qao+n+qbq+pdqV4jW4XvcAF03+UinVraXcl+\nEPsxhZSJnWe92R8w1XAxOW3aTcR6JO7WkD5iBpSI/DmAbwPYC2CNiNyvqhs7vvxjACkHFHknfJeL\naC3tmbglk9dTSBnZeYbkq02vwsXYtGms48y5QDbtxKug7gUwR1WbOtYq/U5ELlXVVQDS8H/T7BGt\npf39waFDGwF7Wtp7y48ppIzpPIsi2WqzN+Hy9NoVwOn67l8YWoQvrFjbeR1PxWr97nZybJr+h57l\n4gVUjjutp6ofi8hiOCE1AQyotBJ5/ypaS7vNi4aj8WsKKW07z3rQm2oz6Xtfp+vxzyMmdHv6eydr\nEx9oIqK1fmf4uUjZKl5AHRORK1T1HQDoqKRuAfAYgPT4FKOoorW0Rzu40faw8mMKKW06z5JgbcNC\nMtj6nZXiBdTXALSGP6GqrQC+JiKP+joqClSsgxsbzlR3vsbWQxu9bIXPiA/yKKxqWEhU3IP6AE7Z\nZYeYAaWqh+N8bXusr1H6i9bSPi9i0bCtgZWKtPwgT5Ct67wAJNj6zSopG3GhLvUosqU9WmClw5Rg\nIqz+IE9RUAuvXR/texW4eA7HWprx9KqwDtKhRfjC0ZIur+06ZQcwkAhgQFEcVTursOX5LWiob0Bh\nUSGWLF2CsqvKugVWXWsdKhBqaQf83+XCT0F/kGeMoUVdGiKOnT2JaXn5mDlwOL5/8FTn899rPQAU\nlXC3BupRvHVQkwGMjpzOE5GFAOpV9UO/B0fmVO2swjMbn8GCuxagaFIR6g/U45knngEAlF3VtVIK\nP1YE6Di0MWyXi3Q9uJGS47aSuyfHPt12AA9JAdAKTM//2Jk7BTD+ZB7K7+cpstSzeBXUvwB4IMrz\nn3Z87fO+jIissOX5LVhw1wKMnTIWADB2ylgsuGsBtmzY0i2gIkUe2tg4ubHbwY2Ztmg460Xu1rCw\nGpWHmjB9clHHC6aZGReltXgBNVpVqyKfVNWqTD5k0Daxptn81lDfgKJJRV2eK5pUhFfqX0nqOpHH\nijjTgaFFw+m4JRMhemNDl90argX+8Ifgx0UZJV5AFcT5Wr7XA6Hukplm81phUSHqD9R3VlAAUH+g\nHoVFhSldN3I6sPpCNRomNXZpaQ9ql4usO468t3hQHxkSL6AqROReVf238CdF5FsAKmP8GfJQKtNs\nqVqydAmeeaJrOL75xJu4ddmtnr5P5LEisQ5u9DqsMnFTWM+F7WnXm4P6BgwdipUnT0Z9nigR8QLq\nOwCeEpGvIBRIcwH0BXCb3wMj76bZesMNwC0btuCV+ldQWFSIW5fd6nswRi4a3nqwGtMidmlPteEi\nUzeFTVncc5GSb/v+2YoVqY0nSayIM0+8hbrHAFwtItcDuLzj6edUdUsgIyPfptkSVXZVWSD3u+KJ\ntgZr1MPr0HAm9FyyLe2ZvClsUno8qM9O3127FudOn+7yXO2ZxcjtPwzPfu+Szop4feUk5Oe14vOz\nDhoaKaUqXpt5fwD3AZgMoArAmo6tjiggQU2zpdNvntECK/LgxkQCK1M3hY0pSlMDkB6BFOnc6dN4\ndERo3KrA+vaReLi+FOsrh2P5nAP4bcUkbNlXjBum1UHVeV3G/rvNYPGm+H4FoAXA7wHcDGA6nGk/\nCkgQ02yvPjcYF5pzcNMdpzt/83zxyaHol9+OxZ870/MFDIsXWBeOO30+0VraM3FT2G6itH5n4mI0\nEWD5yK1YfeYMXqm5F49tL0Fru+DeRTVYPucAAFZT6SpeQM1Q1TIAEJE1AHYEMyQK5+c0mypwoTkH\nb28dCAC46Y7TePHJoXh760B85vqzVldSsYQHVl1rHSr2dW1pB4BxHy/NyE1hez6oL/PCySUCTBry\nAlTvRWu7oK5xYOfX1ldOwis1oWoqLf/dZql4AdXi/oOqtooP/1ZFZCmAVQByAfxSVf/e8zehmESc\nUAKAt7cO7Ayqz1x/trOiSmfhLe2dpwzva8TxUetwrnksRo0agsJr6iEHl6bfprAduzWEB1I2H9Sn\nChz49H/gspHApJFO5f8/fzsUf/O7AgCnUDxwE/TEC3hlu9NFGHQDB/VOvICaJSKfdvyzAMjveCwA\nVFWHpPLGIpIL4BcA/gjAYQA7ReQZVX0vletSctyQcsMJgNXh1NuFy5GnDC8rBQ631OF0eyP2FzoV\n1oDW0o7v29JFwxHrkcoXVgNTEMi5SNEaEwA7PuxVgfUnrkfd2VKUT6vrvAd1368nYuoAwaT+R/Do\nxAqIOPetorW+k53idfHl+vze8wDsV9UDACAi6wAsA8CACpB7zynci08OtTKkvF64PC6vGOPg7HIR\n69BGwOApw7GOoXjADaLgqqPIxgSXiQ/7aOuras+ewKRRe7B8TmhR3YA+DeiDHAicAFs+cqt1/01T\nfCZ3My8GcCjs8WEAn4l8kYiUAygHgDHjxwQzsiSY2orIC244ufecwu9BAfZVUn4uXI52aGNjRGAB\nAZyDFdb6HX23hvQ4hsLPiivWn3e79dZXOh1804b9GzZPrMD6E9fjlUZnDnf5yK0pvTcFy/rjNlR1\nNYDVAFA6p1QND6cLk1sRxRpPMmEpAvTLb+9yz8m9J9Uvv92qcAKCXbgcuYcg0P0cLE/CKlpjQwqL\nY21houJy/3vNz2t1GiJOvACREZ2hlJ9zwbr/pik+kwFVB2B82ONxHc+lDZNbEUWKFpb//tN/x6Bf\nD0Jbe1vMwFr8uTPdDui76Y7TeLeiCqt+aFdlaHrhcniHYPWFagyJOLQxoV3a03RxbDr5/KyDUAVe\n6ZgdddvQGU7px2RA7QQwRUQmwgmmLwO42+B4kmZyK6JIkWF59vRZyGDBmAVjcN2t18Wt7iL/x323\nwq7K0BXUwuVERO4hCHScgzUqYtHwHR91+7O2BZLJBgi/3luEewFmAmMB1dG6/qcAXoDTZv6Yqlb3\n8MesYvo3+nCRYVn5UiUWfWMRmk42ISc3J6nqzqbKMJyp/QETFX4OFgBsdLvtLAukSIlMx/n1Ye/n\nVKDp7kJKndF7UKq6CcAmk2NIhU2/0UeG5Sf1n2DwyMFoPRfanSrR6i6ZyjDoJhEb9gdM1OS5Baj+\n675AS/rvEMYPezLB+iYJm9n0G31kWPbr3w81v6/B7EWzcarhFOoO1eHIB0dQf7geVTur4o4x0crQ\ntiYR2xTkFgA4Z+S9Ta9b8nN6zfT3RsFhQKXI5G/0kdXLjKkzULWhCq/Uv4K+7X1xePthjB07Fs1o\nRk5uDupr6nHNV67BMxvjh0iilaGtU4Fkft2Sn0Fh+nuj4DCg0lS06uXFf30RfVr7ADnAqLGjcMmE\nS/DsPz+LvKF5KLqsCFffcjWmzJ2CI6VH4oZIopWhTU0i2YQVhD3478JfDKg0FVm99B/aH+MWjsPB\ntw9ixY9XdFY9AwcNxH2P3oec3JzOP5tIiCRSGdrUJJJNvK4gTHa7pXunHas5fzGg0lRk9VJ3qA7T\nrpmGD7Z90KVr7/EfPO5biNjUJEK9Z/I3fVYZFA8Dqhds2N4osno533weZ06cwbCiYZ2vKZpUhP79\n+uPNJ97sFiIzps7Aqh+uivs99PR92tQkQkSZhwGVJFs61yKrl6bjTXjnmXew+M7Fna+pP1CPqWVT\nsWTpki4hMmPqDLz3/ntxv4dEv890avvOJuk+dRZPJn9v1BUDKkm2dK5FVi+5ObnQc4qBQweiva29\ny3RbZIis+uGqHr8HW75P6p1MnjrL5O+NumJAJcmmzrXI4KnaWZXQdFtDfQOaPmnCukfW4ZP6TzCs\naBhm3zAbDfUNXV5jy/dJXfWmgvCq24xda12xmvMXAypJNneuJTrdJu2Cbb/bhmu+eQ0KJxWi4UAD\ntj22Dfnt+Z2vsfn7zHa9CQKvus3OnT6Nr584gdaLF7s8/4PaWnx37VrPQ8r2QLRhDJmMAZWkTOhc\ny+mTg4nzJ2JI4RBIjmBI4RBMnD8RDdtDFVQmfJ/kj9aLF3Ft//5dnisFogZJqtjGnd0YUEnKhM61\ntvY2XLHgChz96CjON59H//z+uGLBFdj8+82dr8mE75PsY3tFRHZhQPVCuneuFRYV4mLTRZTNCX0P\nRz440m36Lt2/T9OK+xSj34SPsfqeT6zf0Two6VwRMVyDx4DKQpy+C1BBAYBPTI+CepBI+KRzuKYr\nBpTPbFjUG4nTd9n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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1073,16 +1046,14 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1101,10 +1072,8 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 24, + "metadata": {}, "outputs": [ { "data": { @@ -1114,7 +1083,7 @@ " 0.01635336, 0.01284271, 0.00642076])" ] }, - "execution_count": 23, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1142,10 +1111,8 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "collapsed": false - }, + "execution_count": 25, + "metadata": {}, "outputs": [ { "data": { @@ -1154,7 +1121,7 @@ "" ] }, - "execution_count": 24, + "execution_count": 25, "metadata": { "image/png": { "width": 400 @@ -1191,10 +1158,8 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": { - "collapsed": false - }, + "execution_count": 26, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1230,10 +1195,8 @@ }, { "cell_type": "code", - "execution_count": 26, - "metadata": { - "collapsed": false - }, + "execution_count": 27, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1265,10 +1228,8 @@ }, { "cell_type": "code", - "execution_count": 27, - "metadata": { - "collapsed": false - }, + "execution_count": 28, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1285,10 +1246,8 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, + "execution_count": 29, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1317,10 +1276,8 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false - }, + "execution_count": 30, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1368,9 +1325,7 @@ { "cell_type": "code", "execution_count": 31, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [], "source": [ "eigen_vals, eigen_vecs = np.linalg.eig(np.linalg.inv(S_W).dot(S_B))" @@ -1397,9 +1352,7 @@ { "cell_type": "code", "execution_count": 32, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1409,17 +1362,17 @@ "\n", "452.721581245\n", "156.43636122\n", - "8.11327596465e-14\n", - "2.78687384543e-14\n", - "2.78687384543e-14\n", - "2.27622032758e-14\n", - "2.27622032758e-14\n", - "1.97162599817e-14\n", - "1.32484714652e-14\n", - "1.32484714652e-14\n", - "1.03791501611e-14\n", - "5.94140664834e-15\n", - "2.12636975748e-16\n" + "1.05646703435e-13\n", + "3.99641853702e-14\n", + "3.40923565291e-14\n", + "2.84217094304e-14\n", + "1.4793035293e-14\n", + "1.4793035293e-14\n", + "1.3494134504e-14\n", + "1.3494134504e-14\n", + "6.49105985585e-15\n", + "6.49105985585e-15\n", + "2.65581215704e-15\n" ] } ], @@ -1441,15 +1394,13 @@ { "cell_type": "code", "execution_count": 33, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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904CHgO8TmoZ+kZnNcvcVMcrdBcyrSvAiIpK49PT0Go1NmAqJjN03B3gXWAZU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\nDB/Tgd1R60uI/UdodJno9+I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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1477,28 +1428,26 @@ { "cell_type": "code", "execution_count": 34, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Matrix W:\n", - " [[ 0.0662 -0.3797]\n", - " [-0.0386 -0.2206]\n", - " [ 0.0217 -0.3816]\n", - " [-0.184 0.3018]\n", - " [ 0.0034 0.0141]\n", - " [-0.2326 0.0234]\n", - " [ 0.7747 0.1869]\n", - " [ 0.0811 0.0696]\n", - " [-0.0875 0.1796]\n", - " [-0.185 -0.284 ]\n", - " [ 0.066 0.2349]\n", - " [ 0.3805 0.073 ]\n", - " [ 0.3285 -0.5971]]\n" + " [[-0.0662 -0.3797]\n", + " [ 0.0386 -0.2206]\n", + " [-0.0217 -0.3816]\n", + " [ 0.184 0.3018]\n", + " [-0.0034 0.0141]\n", + " [ 0.2326 0.0234]\n", + " [-0.7747 0.1869]\n", + " [-0.0811 0.0696]\n", + " [ 0.0875 0.1796]\n", + " [ 0.185 -0.284 ]\n", + " [-0.066 0.2349]\n", + " [-0.3805 0.073 ]\n", + " [-0.3285 -0.5971]]\n" ] } ], @@ -1525,16 +1474,14 @@ }, { "cell_type": "code", - "execution_count": 40, - "metadata": { - "collapsed": false - }, + "execution_count": 35, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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A9fqZZ4Cf/tT564wePRo33HADTjjhBADA+eefj/e///343e9+5/i1mKSIiHzi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\nIvKs/w+LR53aVNWRvwAAAABJRU5ErkJggg==\n", 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TEXUwES9bLzjn5A/39fW1P8z3ox/9CF/96lexdetWDA0NAQA+//nP49Zbb82p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\nlRigiIjISv8fciWbSDryTuMAAAAASUVORK5CYII=\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1576,13 +1523,14 @@ }, { "cell_type": "code", - "execution_count": 41, - "metadata": { - "collapsed": false - }, + "execution_count": 36, + "metadata": {}, "outputs": [], "source": [ - "from sklearn.lda import LDA\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.lda import LDA\n", + "else:\n", + " from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\n", "\n", "lda = LDA(n_components=2)\n", "X_train_lda = lda.fit_transform(X_train_std, y_train)" @@ -1590,16 +1538,14 @@ }, { "cell_type": "code", - "execution_count": 42, - "metadata": { - "collapsed": false - }, + "execution_count": 37, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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EOgH4AsCvNbeHe/cREZG5ONxHRETGYkgREZGxGFJERGQshhQRERmL\nIUVERMZiSBERkbEYUkQpIiKHQ9w3T0S+9u2Vtl1EXhWRkWF+/ioR+aeINItIifMtJtKPIUWUOuEW\nJf5JKVWilCqGtV/kShHpE+K6KgC/APC+Uw0kMg1DisggSqklAN4BcG2Ix7YrpXbCOzuGEEXFkCIy\nz2YAXjkckCgpDCki87CnROTDkCIyzxkw4NhuIhMwpIhSJ1wPqfV+EbkS1gGVLyf4XESewl3QiVJE\nRJoA7EHb6cJ/AtATwI0A6gB0A/BPWKcObwvx85fDOp6kL4BDAD5WSv08Na0n0oMhRURExuJwHxER\nGYshRURExmJIERGRsRhSRERkLIYUEREZiyFFRETGYkgREZGx/j89/b2BKlRrvQAAAABJRU5ErkJg\ngg==\n", + "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1622,16 +1568,14 @@ }, { "cell_type": "code", - "execution_count": 43, - "metadata": { - "collapsed": false - }, + "execution_count": 38, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1670,9 +1614,7 @@ { "cell_type": "code", "execution_count": 39, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1711,7 +1653,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 40, "metadata": { "collapsed": true }, @@ -1719,7 +1661,7 @@ "source": [ "from scipy.spatial.distance import pdist, squareform\n", "from scipy import exp\n", - "from scipy.linalg import eigh\n", + "from numpy.linalg import eigh\n", "import numpy as np\n", "\n", "def rbf_kernel_pca(X, gamma, n_components):\n", @@ -1758,7 +1700,7 @@ " K = K - one_n.dot(K) - K.dot(one_n) + one_n.dot(K).dot(one_n)\n", "\n", " # Obtaining eigenpairs from the centered kernel matrix\n", - " # numpy.eigh returns them in sorted order\n", + " # numpy.linalg.eigh returns them in sorted order\n", " eigvals, eigvecs = eigh(K)\n", "\n", " # Collect the top k eigenvectors (projected samples)\n", @@ -1784,16 +1726,14 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": { - "collapsed": false - }, + "execution_count": 41, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1816,16 +1756,14 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 42, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1864,16 +1802,14 @@ }, { "cell_type": "code", - "execution_count": 36, - "metadata": { - "collapsed": false - }, + "execution_count": 43, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1925,16 +1861,14 @@ }, { "cell_type": "code", - "execution_count": 37, - "metadata": { - "collapsed": false - }, + "execution_count": 44, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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FSQyUmVpfH3DxIl+GwUH/fKQwsnPneAwMUHMKIztFJIQRUEsLNZf9+4HOYeWO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\nNzuO02aMmQHgFWPMAcdxtqY7UIVCoVAUF4zjONntwJjNAP7WcZwdEdb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qkHfq6YFxctOLRhkhhZmIeNQSBQLQtGxvt89Dz8Ccb9Q0c13Xx4noESL6NRGd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\nG2GYJiYwTvv7w4u9miHZDUAKNxRVJIlURjjygUyhlV/Hm5jglOBhlH3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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1956,16 +1890,14 @@ }, { "cell_type": "code", - "execution_count": 38, - "metadata": { - "collapsed": false - }, + "execution_count": 45, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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2xiZO5GfZ2UwzzM5mbwiQsXFBEEaMiHggAs1gdemldKE++CBVrK2NA8LGmj77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\n7nMArgUwOkTcmY+dkUGr2oyJ+0+NORjBxnZTUuj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8fKeTp/O995g95fWyCN3ChcDFF3N9dqt+yuLxAI89xgPs6eEJeeopYPduBjE2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\nDmpC5Ohz+t3vmhgG3Xmus9OUyLVb6KdOUbwTEjg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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2001,16 +1933,14 @@ }, { "cell_type": "code", - "execution_count": 39, - "metadata": { - "collapsed": false - }, + "execution_count": 46, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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HRHaF9t1ljPnDKD/GmKaiggK+bx+t7FOngK98BfjSlzhH7U5HOmsW8Npr/Bw7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\nizc1MQObNyNcODd7vNabxxJ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g4pZbuEbc76dYLlrE/d5gMhsUd/x4/8QzJ0/Sc3DRRXTP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\nY06JyEwAG4wx14fOuw7AIwB8AJ4wxvxLaP9FAP4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bOXZqqhP7VxTlwmBCxV1ErgfwAwA+AD82xmyJ+lwin98AoBvAl4wxu0VkHoCn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\nD4cpzLZKXVcXk+eCQT7njBl8ziTXUtsWuwEGPlN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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2059,7 +1989,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 47, "metadata": { "collapsed": true }, @@ -2124,7 +2054,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 48, "metadata": { "collapsed": true }, @@ -2136,64 +2066,58 @@ }, { "cell_type": "code", - "execution_count": 42, - "metadata": { - "collapsed": false - }, + "execution_count": 49, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([ 1.8713, 0.0093])" + "array([ 0.4816, -0.3551])" ] }, - "execution_count": 42, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "x_new = X[25]\n", + "x_new = X[-1]\n", "x_new" ] }, { "cell_type": "code", - "execution_count": 43, - "metadata": { - "collapsed": false - }, + "execution_count": 50, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([ 0.0788])" + "array([ 0.1192])" ] }, - "execution_count": 43, + "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "x_proj = alphas[25] # original projection\n", + "x_proj = alphas[-1] # original projection\n", "x_proj" ] }, { "cell_type": "code", - "execution_count": 44, - "metadata": { - "collapsed": false - }, + "execution_count": 51, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([ 0.0788])" + "array([ 0.1192])" ] }, - "execution_count": 44, + "execution_count": 51, "metadata": {}, "output_type": "execute_result" } @@ -2211,16 +2135,14 @@ }, { "cell_type": "code", - "execution_count": 46, - "metadata": { - "collapsed": false - }, + "execution_count": 52, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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E8ePHUVRUhE2bNjGcrjB+jaBEJATAIQA3AygE8DmA8ap60KHMKAAzVXWUiAwA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\nc0Vkr3W71tg931R9FpGeIrJ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VFTFq1KjYJTaiv83Kz8/n7LPPZuLEifTr149rrrmG4uLi2HyjZxsYOnQo69atA6CwsJDx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\nBTgPeMPM3orM90LgYzNbAbw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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2243,6 +2165,88 @@ "plt.show()" ] }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "X, y = make_moons(n_samples=100, random_state=123)\n", + "alphas, lambdas = rbf_kernel_pca(X[:-1, :], gamma=15, n_components=1)\n", + "\n", + "def project_x(x_new, X, gamma, alphas, lambdas):\n", + " pair_dist = np.array([np.sum((x_new - row)**2) for row in X])\n", + " k = np.exp(-gamma * pair_dist)\n", + " return k.dot(alphas / lambdas)\n", + "\n", + "# projection of the \"new\" datapoint\n", + "x_new = X[-1]\n", + "\n", + "x_reproj = project_x(x_new, X[:-1], gamma=15, alphas=alphas, lambdas=lambdas)\n", + "\n", + "\n", + "plt.scatter(alphas[y[:-1] == 0, 0], np.zeros((50)),\n", + " color='red', marker='^', alpha=0.5)\n", + "plt.scatter(alphas[y[:-1] == 1, 0], np.zeros((49)),\n", + " color='blue', marker='o', alpha=0.5)\n", + "plt.scatter(x_reproj, 0, color='green',\n", + " label='new point [ 100.0, 100.0]', marker='x', s=500)\n", + "plt.legend(scatterpoints=1)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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ZE8xv1Sp4S+/ZA02bBuuAIJyOHAmW1ahR8GG3bFmwzE2boEGacUWTiWQfGMvM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\ns1x3z6m6Zt1SH8dVH8cE9XN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+ "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(alphas[y[:-1] == 0, 0], np.zeros((50)),\n", + " color='red', marker='^', alpha=0.5)\n", + "plt.scatter(alphas[y[:-1] == 1, 0], np.zeros((49)),\n", + " color='blue', marker='o', alpha=0.5)\n", + "plt.scatter(x_proj, 0, color='black',\n", + " label='some point [1.8713, 0.0093]', marker='^', s=100)\n", + "plt.scatter(x_reproj, 0, color='green',\n", + " label='new point [ 100.0, 100.0]', marker='x', s=500)\n", + "plt.legend(scatterpoints=1)\n", + "\n", + "plt.tight_layout()\n", + "# plt.savefig('./figures/reproject.png', dpi=300)\n", + "plt.show()" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -2260,16 +2264,14 @@ }, { "cell_type": "code", - "execution_count": 47, - "metadata": { - "collapsed": false - }, + "execution_count": 55, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -2323,6 +2325,7 @@ } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "language": "python", @@ -2338,9 +2341,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.0" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch06/ch06.ipynb b/code/ch06/ch06.ipynb index 3094ac6b..67aeaf62 100644 --- a/code/ch06/ch06.ipynb +++ b/code/ch06/ch06.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Copyright (c) 2015, 2016 [Sebastian Raschka](sebastianraschka.com)\n", + "Copyright (c) 2015 - 2017 [Sebastian Raschka](sebastianraschka.com)\n", "\n", "https://github.com/rasbt/python-machine-learning-book\n", "\n", @@ -35,30 +35,28 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-03-25 \n", + "last updated: 2017-04-09 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.0.3\n", + "CPython 3.5.2\n", + "IPython 5.3.0\n", "\n", - "numpy 1.10.4\n", - "pandas 0.17.1\n", - "matplotlib 1.5.1\n", - "scikit-learn 0.17.1\n" + "numpy 1.12.1\n", + "pandas 0.19.2\n", + "matplotlib 2.0.0\n", + "sklearn 0.19.dev0\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scikit-learn" + "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,sklearn" ] }, { @@ -119,24 +117,27 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "from IPython.display import Image" + "from IPython.display import Image\n", + "%matplotlib inline" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "%matplotlib inline" + "# Added version check for recent scikit-learn 0.18 checks\n", + "from distutils.version import LooseVersion as Version\n", + "from sklearn import __version__ as sklearn_version" ] }, { @@ -163,10 +164,15 @@ { "cell_type": "code", "execution_count": 4, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "rows, columns: (569, 32)\n" + ] + }, { "data": { "text/html": [ @@ -356,17 +362,25 @@ ], "source": [ "import pandas as pd\n", + "import urllib\n", "\n", - "df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases'\n", - " '/breast-cancer-wisconsin/wdbc.data', header=None)" + "try:\n", + " df = pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases'\n", + " '/breast-cancer-wisconsin/wdbc.data', header=None)\n", + "\n", + "except urllib.error.URLError:\n", + " df = pd.read_csv('https://raw.githubusercontent.com/rasbt/'\n", + " 'python-machine-learning-book/master/code/'\n", + " 'datasets/wdbc/wdbc.data', header=None)\n", + " \n", + "print('rows, columns:', df.shape)\n", + "df.head()" ] }, { "cell_type": "code", "execution_count": 5, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -383,232 +397,10 @@ "df.shape" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - "\n", - "### Note:\n", - "\n", - "\n", - "If the link to the Breast Cancer Wisconsin dataset dataset provided above does not work for you, you can find a local copy in this repository at [./../datasets/wdbc/wdbc.data](./../datasets/wdbc/wdbc.data).\n", - "\n", - "Or you could fetch it via" - ] - }, { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " 0 1 2 3 4 5 6 7 8 \\\n", - "0 842302 M 17.99 10.38 122.80 1001.0 0.11840 0.27760 0.3001 \n", - "1 842517 M 20.57 17.77 132.90 1326.0 0.08474 0.07864 0.0869 \n", - "2 84300903 M 19.69 21.25 130.00 1203.0 0.10960 0.15990 0.1974 \n", - "3 84348301 M 11.42 20.38 77.58 386.1 0.14250 0.28390 0.2414 \n", - "4 84358402 M 20.29 14.34 135.10 1297.0 0.10030 0.13280 0.1980 \n", - "\n", - " 9 ... 22 23 24 25 26 27 28 \\\n", - "0 0.14710 ... 25.38 17.33 184.60 2019.0 0.1622 0.6656 0.7119 \n", - "1 0.07017 ... 24.99 23.41 158.80 1956.0 0.1238 0.1866 0.2416 \n", - "2 0.12790 ... 23.57 25.53 152.50 1709.0 0.1444 0.4245 0.4504 \n", - "3 0.10520 ... 14.91 26.50 98.87 567.7 0.2098 0.8663 0.6869 \n", - "4 0.10430 ... 22.54 16.67 152.20 1575.0 0.1374 0.2050 0.4000 \n", - "\n", - " 29 30 31 \n", - "0 0.2654 0.4601 0.11890 \n", - "1 0.1860 0.2750 0.08902 \n", - "2 0.2430 0.3613 0.08758 \n", - "3 0.2575 0.6638 0.17300 \n", - "4 0.1625 0.2364 0.07678 \n", - "\n", - "[5 rows x 32 columns]" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df = pd.read_csv('https://raw.githubusercontent.com/rasbt/python-machine-learning-book/master/code/datasets/wdbc/wdbc.data', header=None)\n", - "df.head()" - ] - }, - { - "cell_type": "markdown", "metadata": {}, - "source": [ - "
" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, "outputs": [ { "data": { @@ -616,13 +408,14 @@ "array([1, 0])" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.preprocessing import LabelEncoder\n", + "\n", "X = df.loc[:, 2:].values\n", "y = df.loc[:, 1].values\n", "le = LabelEncoder()\n", @@ -632,13 +425,14 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [], "source": [ - "from sklearn.cross_validation import train_test_split\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", "\n", "X_train, X_test, y_train, y_test = \\\n", " train_test_split(X, y, test_size=0.20, random_state=1)" @@ -661,10 +455,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -691,10 +483,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { @@ -703,7 +493,7 @@ "" ] }, - "execution_count": 10, + "execution_count": 9, "metadata": { "image/png": { "width": 500 @@ -747,10 +537,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "data": { @@ -759,7 +547,7 @@ "" ] }, - "execution_count": 11, + "execution_count": 10, "metadata": { "image/png": { "width": 500 @@ -789,10 +577,8 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { @@ -801,7 +587,7 @@ "" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": { "image/png": { "width": 500 @@ -816,10 +602,8 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -842,11 +626,20 @@ ], "source": [ "import numpy as np\n", - "from sklearn.cross_validation import StratifiedKFold\n", "\n", - "kfold = StratifiedKFold(y=y_train, \n", - " n_folds=10,\n", - " random_state=1)\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import StratifiedKFold\n", + "else:\n", + " from sklearn.model_selection import StratifiedKFold\n", + " \n", + "\n", + "if Version(sklearn_version) < '0.18':\n", + " kfold = StratifiedKFold(y=y_train, \n", + " n_folds=10,\n", + " random_state=1)\n", + "else:\n", + " kfold = StratifiedKFold(n_splits=10,\n", + " random_state=1).split(X_train, y_train)\n", "\n", "scores = []\n", "for k, (train, test) in enumerate(kfold):\n", @@ -861,10 +654,8 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -877,7 +668,10 @@ } ], "source": [ - "from sklearn.cross_validation import cross_val_score\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import cross_val_score\n", + "else:\n", + " from sklearn.model_selection import cross_val_score\n", "\n", "scores = cross_val_score(estimator=pipe_lr,\n", " X=X_train,\n", @@ -920,10 +714,8 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { @@ -932,7 +724,7 @@ "" ] }, - "execution_count": 15, + "execution_count": 14, "metadata": { "image/png": { "width": 600 @@ -947,16 +739,14 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { - 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r79vj8uD3+Pv1iaSdMbVJXUsdpjYpSi+iKL1ov7cwiVJKke5NJ92bTklmCXWB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\nRJ+kk0gOYIGZtXt2MTZspK80G7qmN4GngE9RkP0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25d+ybs869vXsG3S56+ZfVz6/NXXM1MNO1ifK723W12YNuLzeeXh5pBbuB7UL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\n2bhxIxERERw8eJCSkhLatm0bsJ+NGzcyZcoUAHr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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -965,7 +755,13 @@ ], "source": [ "import matplotlib.pyplot as plt\n", - "from sklearn.learning_curve import learning_curve\n", + "\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.learning_curve import learning_curve\n", + "else:\n", + " from sklearn.model_selection import learning_curve\n", + "\n", + "\n", "\n", "pipe_lr = Pipeline([('scl', StandardScaler()),\n", " ('clf', LogisticRegression(penalty='l2', random_state=0))])\n", @@ -1029,16 +825,14 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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elqLSG+z8McZQ7C6m2F3M9IrpPZ4/sWQiS2YssQJaWx2b9m+irq2Og8cezHeP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\nTcpYU0PfJyLLhjotucgYUwr8RES+PNRpyUXGmMd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bL5t1ve7GjnUdHLbsGXw7PPdvby5pe/t2vnzKl7nypCt5R+M7+M653+Edje/I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\n+qy9AAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1046,7 +840,12 @@ } ], "source": [ - "from sklearn.learning_curve import validation_curve\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.learning_curve import validation_curve\n", + "else:\n", + " from sklearn.model_selection import validation_curve\n", + "\n", + "\n", "\n", "param_range = [0.001, 0.01, 0.1, 1.0, 10.0, 100.0]\n", "train_scores, test_scores = validation_curve(\n", @@ -1123,10 +922,8 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1138,8 +935,11 @@ } ], "source": [ - "from sklearn.grid_search import GridSearchCV\n", "from sklearn.svm import SVC\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.grid_search import GridSearchCV\n", + "else:\n", + " from sklearn.model_selection import GridSearchCV\n", "\n", "pipe_svc = Pipeline([('scl', StandardScaler()),\n", " ('clf', SVC(random_state=1))])\n", @@ -1164,10 +964,8 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1200,10 +998,8 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "data": { @@ -1212,7 +1008,7 @@ "" ] }, - "execution_count": 20, + "execution_count": 19, "metadata": { "image/png": { "width": 500 @@ -1227,10 +1023,8 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "collapsed": false - }, + "execution_count": 20, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1256,10 +1050,8 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1271,6 +1063,7 @@ ], "source": [ "from sklearn.tree import DecisionTreeClassifier\n", + "\n", "gs = GridSearchCV(estimator=DecisionTreeClassifier(random_state=0),\n", " param_grid=[{'max_depth': [1, 2, 3, 4, 5, 6, 7, None]}],\n", " scoring='accuracy',\n", @@ -1310,10 +1103,8 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { @@ -1322,7 +1113,7 @@ "" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": { "image/png": { "width": 300 @@ -1337,10 +1128,8 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1353,6 +1142,7 @@ ], "source": [ "from sklearn.metrics import confusion_matrix\n", + "\n", "pipe_svc.fit(X_train, y_train)\n", "y_pred = pipe_svc.predict(X_test)\n", "confmat = confusion_matrix(y_true=y_test, y_pred=y_pred)\n", @@ -1361,16 +1151,14 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": { - "collapsed": false - }, + "execution_count": 24, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1408,10 +1196,8 @@ }, { "cell_type": "code", - "execution_count": 26, - "metadata": { - "collapsed": false - }, + "execution_count": 25, + "metadata": {}, "outputs": [ { "data": { @@ -1419,7 +1205,7 @@ "array([1, 0])" ] }, - "execution_count": 26, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -1430,10 +1216,8 @@ }, { "cell_type": "code", - "execution_count": 27, - "metadata": { - "collapsed": false - }, + "execution_count": 26, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1458,10 +1242,8 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, + "execution_count": 27, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1486,10 +1268,8 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false - }, + "execution_count": 28, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1531,10 +1311,8 @@ }, { "cell_type": "code", - "execution_count": 30, - "metadata": { - "collapsed": false - }, + "execution_count": 29, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1556,17 +1334,15 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": { - "collapsed": false - }, + "execution_count": 30, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.982798668208\n", - "{'clf__C': 0.1, 'clf__kernel': 'linear'}\n" + "{'clf__kernel': 'linear', 'clf__C': 0.1}\n" ] } ], @@ -1610,16 +1386,14 @@ }, { "cell_type": "code", - "execution_count": 40, - "metadata": { - "collapsed": false - }, + "execution_count": 31, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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eiSv/phNdKz9SWFjIihUrOHHiBGPGjOHss8+2OiQVoLRjmwpqOTk5LFu2zOow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VSrXEnLjvAu4usc9J4FYgTinVCGgHHHVgTEK4jby8PO68806u/XKNJ598kvj4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\nHwdT0ZXBwGlzAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1638,7 +1412,15 @@ "\n", "X_train2 = X_train[:, [4, 14]]\n", "\n", - "cv = StratifiedKFold(y_train, n_folds=3, random_state=1)\n", + "\n", + "if Version(sklearn_version) < '0.18':\n", + " cv = StratifiedKFold(y_train, \n", + " n_folds=3, \n", + " random_state=1)\n", + " \n", + "else:\n", + " cv = list(StratifiedKFold(n_splits=3, \n", + " random_state=1).split(X_train, y_train))\n", "\n", "fig = plt.figure(figsize=(7, 5))\n", "\n", @@ -1694,36 +1476,35 @@ }, { "cell_type": "code", - "execution_count": 41, - "metadata": { - "collapsed": false - }, + "execution_count": 32, + "metadata": {}, "outputs": [], "source": [ "pipe_lr = pipe_lr.fit(X_train2, y_train)\n", - "y_pred2 = pipe_lr.predict(X_test[:, [4, 14]])" + "y_labels = pipe_lr.predict(X_test[:, [4, 14]])\n", + "y_probas = pipe_lr.predict_proba(X_test[:, [4, 14]])[:, 1]\n", + "# note that we use probabilities for roc_auc\n", + "# the `[:, 1]` selects the positive class label only" ] }, { "cell_type": "code", - "execution_count": 42, - "metadata": { - "collapsed": false - }, + "execution_count": 33, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "ROC AUC: 0.662\n", + "ROC AUC: 0.752\n", "Accuracy: 0.711\n" ] } ], "source": [ "from sklearn.metrics import roc_auc_score, accuracy_score\n", - "print('ROC AUC: %.3f' % roc_auc_score(y_true=y_test, y_score=y_pred2))\n", - "print('Accuracy: %.3f' % accuracy_score(y_true=y_test, y_pred=y_pred2))" + "print('ROC AUC: %.3f' % roc_auc_score(y_true=y_test, y_score=y_probas))\n", + "print('Accuracy: %.3f' % accuracy_score(y_true=y_test, y_pred=y_labels))" ] }, { @@ -1743,10 +1524,8 @@ }, { "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, + "execution_count": 34, + "metadata": {}, "outputs": [], "source": [ "pre_scorer = make_scorer(score_func=precision_score, \n", @@ -1776,43 +1555,28 @@ "source": [ "..." ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - "
" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "
\n", - "
" - ] } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 2", + "display_name": "Python [default]", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch07/ch07.ipynb b/code/ch07/ch07.ipynb index 94f9197a..9aae104c 100644 --- a/code/ch07/ch07.ipynb +++ b/code/ch07/ch07.ipynb @@ -44,22 +44,22 @@ "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-06-11 \n", + "last updated: 2016-09-29 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.2.0\n", + "CPython 3.5.2\n", + "IPython 5.1.0\n", "\n", - "numpy 1.11.0\n", - "pandas 0.18.0\n", + "numpy 1.11.1\n", + "pandas 0.18.1\n", "matplotlib 1.5.1\n", - "scipy 0.17.1\n", - "scikit-learn 0.17.1\n" + "scipy 0.18.1\n", + "sklearn 0.18\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scipy,scikit-learn" + "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scipy,sklearn" ] }, { @@ -115,7 +115,8 @@ }, "outputs": [], "source": [ - "from IPython.display import Image" + "from IPython.display import Image\n", + "%matplotlib inline" ] }, { @@ -126,7 +127,9 @@ }, "outputs": [], "source": [ - "%matplotlib inline" + "# Added version check for recent scikit-learn 0.18 checks\n", + "from distutils.version import LooseVersion as Version\n", + "from sklearn import __version__ as sklearn_version" ] }, { @@ -219,7 +222,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "collapsed": true }, @@ -237,7 +240,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "collapsed": false }, @@ -248,7 +251,7 @@ "0.034327507019042969" ] }, - "execution_count": 9, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" } @@ -259,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 9, "metadata": { "collapsed": false }, @@ -274,7 +277,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 10, "metadata": { "collapsed": false }, @@ -283,7 +286,7 @@ "data": { "image/png": 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HjDG7gbNY7VLi7959SqnMmTYNIiKgVCkYOdLpaCx/HviTcX+MI19QPoY0HcLL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\nUOm95BstJ3ul1yZl0nif2nZ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PU7pQad5r+x7drummA3RTcfIktG5tJajatWHxYk1QSuU1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\nSkhFRES1vgOJtW1JroE8AwAAAABJRU5ErkJggg=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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -330,7 +333,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 11, "metadata": { "collapsed": false }, @@ -341,7 +344,7 @@ "1" ] }, - "execution_count": 10, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -355,7 +358,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 12, "metadata": { "collapsed": false }, @@ -366,7 +369,7 @@ "array([ 0.58, 0.42])" ] }, - "execution_count": 11, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -384,7 +387,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 13, "metadata": { "collapsed": false }, @@ -395,7 +398,7 @@ "0" ] }, - "execution_count": 12, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -406,7 +409,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 14, "metadata": { "collapsed": true }, @@ -567,16 +570,19 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 15, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn import datasets\n", - "from sklearn.cross_validation import train_test_split\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.preprocessing import LabelEncoder\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", "\n", "iris = datasets.load_iris()\n", "X, y = iris.data[50:, [1, 2]], iris.target[50:]\n", @@ -591,7 +597,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 16, "metadata": { "collapsed": false }, @@ -609,12 +615,15 @@ } ], "source": [ - "from sklearn.cross_validation import cross_val_score\n", + "import numpy as np\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.neighbors import KNeighborsClassifier \n", "from sklearn.pipeline import Pipeline\n", - "import numpy as np\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import cross_val_score\n", + "else:\n", + " from sklearn.model_selection import cross_val_score\n", "\n", "clf1 = LogisticRegression(penalty='l2', \n", " C=0.001,\n", @@ -648,7 +657,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -699,16 +708,16 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 18, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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bBlhKglyOZdPwVqXUVhGJL99x2rRpREVFARAWFkZ0dDRDSqoAlr7A7mjnF+QT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\n0KCBHj9+XK9du6YdO3bUSZMmqarqkSNHtGrVqrpz507NzMz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i3BZ72AD8/aFmTZs2USrONA9pC5xVv5iYGD7//HNdbN6BAwdWyHmbs+pnDdxZ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\nx4/nwIED7Nixg8LCQj766CPq1q2r++3m5OTwxx9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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -755,7 +764,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 19, "metadata": { "collapsed": true }, @@ -767,16 +776,16 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 20, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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N0JnRSo8en2Hjtk+J8WNA2Lj9Hnbb7TMpy27atI5I5D5UVwM/BwTViSxbNpBR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\nbClb/vnPPxONbqGq6uY226PRKE8/3cPXAwSg7o1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MqMV351niYeCRnbW1jVWR/cvLGZOhqshCZHf6JtMsZ4OTiTt9K/RNaFnVX/Cs0DeZZDkb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\n+v287FhVV3uKoPm+TwFeBt7BubBQ4Fe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jhnO2TmXK2xFb6DdzqN92xZTOczqw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\nrEv8PzjZkPV+jleSAAAAAElFTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -839,7 +848,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 21, "metadata": { "collapsed": false }, @@ -848,7 +857,8 @@ "data": { "text/plain": [ "{'decisiontreeclassifier': DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=1,\n", - " max_features=None, max_leaf_nodes=None, min_samples_leaf=1,\n", + " max_features=None, max_leaf_nodes=None,\n", + " min_impurity_split=1e-07, min_samples_leaf=1,\n", " min_samples_split=2, min_weight_fraction_leaf=0.0,\n", " presort=False, random_state=0, splitter='best'),\n", " 'decisiontreeclassifier__class_weight': None,\n", @@ -856,6 +866,7 @@ " 'decisiontreeclassifier__max_depth': 1,\n", " 'decisiontreeclassifier__max_features': None,\n", " 'decisiontreeclassifier__max_leaf_nodes': None,\n", + " 'decisiontreeclassifier__min_impurity_split': 1e-07,\n", " 'decisiontreeclassifier__min_samples_leaf': 1,\n", " 'decisiontreeclassifier__min_samples_split': 2,\n", " 'decisiontreeclassifier__min_weight_fraction_leaf': 0.0,\n", @@ -921,7 +932,7 @@ " weights='uniform')]]}" ] }, - "execution_count": 48, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -932,7 +943,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 22, "metadata": { "collapsed": false }, @@ -941,17 +952,20 @@ "name": "stdout", "output_type": "stream", "text": [ - "0.967+/-0.05 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.001}\n", - "0.967+/-0.05 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.1}\n", - "1.000+/-0.00 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 100.0}\n", - "0.967+/-0.05 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.001}\n", - "0.967+/-0.05 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.1}\n", - "1.000+/-0.00 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 100.0}\n" + "0.967 +/- 0.05 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.001}\n", + "0.967 +/- 0.05 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 0.1}\n", + "1.000 +/- 0.00 {'decisiontreeclassifier__max_depth': 1, 'pipeline-1__clf__C': 100.0}\n", + "0.967 +/- 0.05 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.001}\n", + "0.967 +/- 0.05 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 0.1}\n", + "1.000 +/- 0.00 {'decisiontreeclassifier__max_depth': 2, 'pipeline-1__clf__C': 100.0}\n" ] } ], "source": [ - "from sklearn.grid_search import GridSearchCV\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import GridSearchCV\n", + "else:\n", + " from sklearn.model_selection import GridSearchCV\n", "\n", "params = {'decisiontreeclassifier__max_depth': [1, 2],\n", " 'pipeline-1__clf__C': [0.001, 0.1, 100.0]}\n", @@ -962,14 +976,25 @@ " scoring='roc_auc')\n", "grid.fit(X_train, y_train)\n", "\n", - "for params, mean_score, scores in grid.grid_scores_:\n", - " print(\"%0.3f+/-%0.2f %r\"\n", - " % (mean_score, scores.std() / 2.0, params))" + "\n", + "if Version(sklearn_version) < '0.18':\n", + " for params, mean_score, scores in grid.grid_scores_:\n", + " print(\"%0.3f +/- %0.2f %r\"\n", + " % (mean_score, scores.std() / 2.0, params))\n", + "\n", + "else:\n", + " cv_keys = ('mean_test_score', 'std_test_score','params')\n", + "\n", + " for r, _ in enumerate(grid.cv_results_['mean_test_score']):\n", + " print(\"%0.3f +/- %0.2f %r\"\n", + " % (grid.cv_results_[cv_keys[0]][r], \n", + " grid.cv_results_[cv_keys[1]][r] / 2.0, \n", + " grid.cv_results_[cv_keys[2]][r]))" ] }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 23, "metadata": { "collapsed": false }, @@ -1007,7 +1032,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 24, "metadata": { "collapsed": false }, @@ -1020,7 +1045,8 @@ " penalty='l2', random_state=0, solver='liblinear', tol=0.0001,\n", " verbose=0, warm_start=False)]]),\n", " DecisionTreeClassifier(class_weight=None, criterion='entropy', max_depth=1,\n", - " max_features=None, max_leaf_nodes=None, min_samples_leaf=1,\n", + " max_features=None, max_leaf_nodes=None,\n", + " min_impurity_split=1e-07, min_samples_leaf=1,\n", " min_samples_split=2, min_weight_fraction_leaf=0.0,\n", " presort=False, random_state=0, splitter='best'),\n", " Pipeline(steps=[['sc', StandardScaler(copy=True, with_mean=True, with_std=True)], ['clf', KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski',\n", @@ -1028,7 +1054,7 @@ " weights='uniform')]])]" ] }, - "execution_count": 34, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -1039,7 +1065,7 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 25, "metadata": { "collapsed": false }, @@ -1050,7 +1076,7 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 26, "metadata": { "collapsed": false }, @@ -1066,7 +1092,7 @@ " vote='classlabel', weights=None)" ] }, - "execution_count": 51, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -1077,7 +1103,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": 27, "metadata": { "collapsed": false }, @@ -1093,7 +1119,7 @@ " vote='classlabel', weights=None)" ] }, - "execution_count": 52, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" } @@ -1119,7 +1145,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 28, "metadata": { "collapsed": false }, @@ -1131,7 +1157,7 @@ "" ] }, - "execution_count": 23, + "execution_count": 28, "metadata": { "image/png": { "width": 500 @@ -1146,7 +1172,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 29, "metadata": { "collapsed": false }, @@ -1158,7 +1184,7 @@ "" ] }, - "execution_count": 24, + "execution_count": 29, "metadata": { "image/png": { "width": 400 @@ -1173,7 +1199,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 30, "metadata": { "collapsed": false }, @@ -1200,14 +1226,18 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 31, "metadata": { "collapsed": false }, "outputs": [], "source": [ "from sklearn.preprocessing import LabelEncoder\n", - "from sklearn.cross_validation import train_test_split\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", + "\n", "\n", "le = LabelEncoder()\n", "y = le.fit_transform(y)\n", @@ -1220,7 +1250,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 32, "metadata": { "collapsed": false }, @@ -1245,7 +1275,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 33, "metadata": { "collapsed": false }, @@ -1283,7 +1313,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 34, "metadata": { "collapsed": false }, @@ -1292,7 +1322,7 @@ "data": { "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1365,7 +1395,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 35, "metadata": { "collapsed": false }, @@ -1377,7 +1407,7 @@ "" ] }, - "execution_count": 33, + "execution_count": 35, "metadata": { "image/png": { "width": 400 @@ -1392,7 +1422,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 36, "metadata": { "collapsed": false }, @@ -1404,7 +1434,7 @@ "" ] }, - "execution_count": 34, + "execution_count": 36, "metadata": { "image/png": { "width": 500 @@ -1419,7 +1449,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 37, "metadata": { "collapsed": true }, @@ -1439,7 +1469,7 @@ }, { "cell_type": "code", - "execution_count": 90, + "execution_count": 38, "metadata": { "collapsed": false }, @@ -1475,7 +1505,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 39, "metadata": { "collapsed": false }, @@ -1484,7 +1514,7 @@ "data": { 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LyOeb2S+Cl/0e4GQz+xVQBXwJ/Ch7EUuuau2xfRFpP5QPtm85U+QA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\nSHrfiYisCwAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1568,7 +1598,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.5.2" } }, "nbformat": 4, diff --git a/code/ch08/ch08.ipynb b/code/ch08/ch08.ipynb index 99ac2145..0be3d989 100644 --- a/code/ch08/ch08.ipynb +++ b/code/ch08/ch08.ipynb @@ -34,34 +34,30 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, + "execution_count": 1, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "The watermark extension is already loaded. To reload it, use:\n", - " %reload_ext watermark\n", "Sebastian Raschka \n", - "last updated: 2016-06-30 \n", + "last updated: 2016-09-29 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.2.0\n", + "CPython 3.5.2\n", + "IPython 5.1.0\n", "\n", - "numpy 1.11.0\n", + "numpy 1.11.1\n", "pandas 0.18.1\n", "matplotlib 1.5.1\n", - "scikit-learn 0.17.1\n", + "sklearn 0.18\n", "nltk 3.2.1\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scikit-learn,nltk" + "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,sklearn,nltk" ] }, { @@ -111,6 +107,19 @@ "
" ] }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "# Added version check for recent scikit-learn 0.18 checks\n", + "from distutils.version import LooseVersion as Version\n", + "from sklearn import __version__ as sklearn_version" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -166,10 +175,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 2, + "metadata": {}, "outputs": [ { "name": "stderr", @@ -177,7 +184,7 @@ "text": [ "0% 100%\n", "[##############################] | ETA: 00:00:00\n", - "Total time elapsed: 00:06:23\n" + "Total time elapsed: 00:09:04\n" ] } ], @@ -215,7 +222,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "collapsed": true }, @@ -236,7 +243,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { "collapsed": true }, @@ -247,10 +254,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { @@ -291,7 +296,7 @@ "2 ***SPOILER*** Do not read this, if you think a... 0" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -356,14 +361,13 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "from sklearn.feature_extraction.text import CountVectorizer\n", + "\n", "count = CountVectorizer()\n", "docs = np.array([\n", " 'The sun is shining',\n", @@ -381,16 +385,14 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "{'sun': 4, 'and': 0, 'is': 1, 'the': 6, 'shining': 3, 'two': 7, 'sweet': 5, 'weather': 8, 'one': 2}\n" + "{'one': 2, 'sweet': 5, 'the': 6, 'shining': 3, 'weather': 8, 'and': 0, 'two': 7, 'is': 1, 'sun': 4}\n" ] } ], @@ -414,10 +416,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -449,7 +449,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "collapsed": true }, @@ -478,10 +478,8 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -546,10 +544,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -594,10 +590,8 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { @@ -605,7 +599,7 @@ "array([ 3.39, 3. , 3.39, 1.29, 1.29, 1.29, 2. , 1.69, 1.29])" ] }, - "execution_count": 13, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -618,10 +612,8 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { @@ -629,7 +621,7 @@ "array([ 0.5 , 0.45, 0.5 , 0.19, 0.19, 0.19, 0.3 , 0.25, 0.19])" ] }, - "execution_count": 14, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -655,10 +647,8 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { @@ -666,7 +656,7 @@ "'is seven.

Title (Brazil): Not Available'" ] }, - "execution_count": 15, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -677,10 +667,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [], "source": [ "import re\n", @@ -694,10 +682,8 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "data": { @@ -705,7 +691,7 @@ "'is seven title brazil not available'" ] }, - "execution_count": 17, + "execution_count": 18, "metadata": {}, "output_type": "execute_result" } @@ -716,10 +702,8 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "data": { @@ -727,7 +711,7 @@ "'this is a test :) :( :)'" ] }, - "execution_count": 18, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -738,10 +722,8 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 20, + "metadata": {}, "outputs": [], "source": [ "df['review'] = df['review'].apply(preprocessor)" @@ -763,7 +745,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 21, "metadata": { "collapsed": true }, @@ -783,10 +765,8 @@ }, { "cell_type": "code", - "execution_count": 21, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { @@ -794,7 +774,7 @@ "['runners', 'like', 'running', 'and', 'thus', 'they', 'run']" ] }, - "execution_count": 21, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -805,10 +785,8 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "data": { @@ -816,7 +794,7 @@ "['runner', 'like', 'run', 'and', 'thu', 'they', 'run']" ] }, - "execution_count": 22, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -827,10 +805,8 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 24, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -847,7 +823,7 @@ "True" ] }, - "execution_count": 23, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -860,10 +836,8 @@ }, { "cell_type": "code", - "execution_count": 24, - "metadata": { - "collapsed": false - }, + "execution_count": 25, + "metadata": {}, "outputs": [ { "data": { @@ -871,7 +845,7 @@ "['runner', 'like', 'run', 'run', 'lot']" ] }, - "execution_count": 24, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -908,10 +882,8 @@ }, { "cell_type": "code", - "execution_count": 25, - "metadata": { - "collapsed": false - }, + "execution_count": 26, + "metadata": {}, "outputs": [], "source": [ "X_train = df.loc[:25000, 'review'].values\n", @@ -922,16 +894,17 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": { - "collapsed": false - }, + "execution_count": 29, + "metadata": {}, "outputs": [], "source": [ - "from sklearn.grid_search import GridSearchCV\n", "from sklearn.pipeline import Pipeline\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.grid_search import GridSearchCV\n", + "else:\n", + " from sklearn.model_selection import GridSearchCV\n", "\n", "tfidf = TfidfVectorizer(strip_accents=None,\n", " lowercase=False,\n", @@ -961,12 +934,17 @@ " n_jobs=-1)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Note:** Some readers [encountered problems](https://github.com/rasbt/python-machine-learning-book/issues/50) running the following code on Windows. Unfortunately, problems with multiprocessing on Windows are not uncommon. So, if the following code cell should result in issues on your machine, try setting `n_jobs=1` (instead of `n_jobs=-1` in the previous code cell)." + ] + }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false - }, + "execution_count": 30, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -979,9 +957,9 @@ "name": "stderr", "output_type": "stream", "text": [ - "[Parallel(n_jobs=-1)]: Done 42 tasks | elapsed: 12.0min\n", - "[Parallel(n_jobs=-1)]: Done 192 tasks | elapsed: 53.2min\n", - "[Parallel(n_jobs=-1)]: Done 240 out of 240 | elapsed: 69.4min finished\n" + "[Parallel(n_jobs=-1)]: Done 42 tasks | elapsed: 43.9min\n", + "[Parallel(n_jobs=-1)]: Done 192 tasks | elapsed: 228.2min\n", + "[Parallel(n_jobs=-1)]: Done 240 out of 240 | elapsed: 265.3min finished\n" ] }, { @@ -995,11 +973,12 @@ " ...nalty='l2', random_state=0, solver='liblinear', tol=0.0001,\n", " verbose=0, warm_start=False))]),\n", " fit_params={}, iid=True, n_jobs=-1,\n", - " param_grid=[{'vect__tokenizer': [, ], 'vect__ngram_range': [(1, 1)], 'clf__C': [1.0, 10.0, 100.0], 'clf__penalty': ['l1', 'l2'], 'vect__stop_words': [['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', 'you...kenizer at 0x111594400>, ], 'clf__penalty': ['l1', 'l2']}],\n", - " pre_dispatch='2*n_jobs', refit=True, scoring='accuracy', verbose=1)" + " param_grid=[{'vect__tokenizer': [, ], 'vect__ngram_range': [(1, 1)], 'vect__stop_words': [['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', '...alty': ['l1', 'l2'], 'vect__norm': [None], 'vect__ngram_range': [(1, 1)], 'vect__use_idf': [False]}],\n", + " pre_dispatch='2*n_jobs', refit=True, return_train_score=True,\n", + " scoring='accuracy', verbose=1)" ] }, - "execution_count": 29, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -1010,16 +989,14 @@ }, { "cell_type": "code", - "execution_count": 30, - "metadata": { - "collapsed": false - }, + "execution_count": 31, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Best parameter set: {'vect__tokenizer': , 'vect__ngram_range': (1, 1), 'clf__C': 10.0, 'clf__penalty': 'l2', 'vect__stop_words': None} \n", + "Best parameter set: {'vect__tokenizer': , 'clf__C': 10.0, 'vect__stop_words': None, 'clf__penalty': 'l2', 'vect__ngram_range': (1, 1)} \n", "CV Accuracy: 0.897\n" ] } @@ -1031,10 +1008,8 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": { - "collapsed": false - }, + "execution_count": 32, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1068,10 +1043,8 @@ }, { "cell_type": "code", - "execution_count": 38, - "metadata": { - "collapsed": false - }, + "execution_count": 36, + "metadata": {}, "outputs": [ { "data": { @@ -1079,23 +1052,33 @@ "array([ 0.6, 0.4, 0.6, 0.2, 0.6])" ] }, - "execution_count": 38, + "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "from sklearn.cross_validation import StratifiedKFold, cross_val_score\n", "from sklearn.linear_model import LogisticRegression\n", "import numpy as np\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import StratifiedKFold\n", + " from sklearn.cross_validation import cross_val_score\n", + "else:\n", + " from sklearn.model_selection import StratifiedKFold\n", + " from sklearn.model_selection import cross_val_score\n", "\n", "np.random.seed(0)\n", "np.set_printoptions(precision=6)\n", "y = [np.random.randint(3) for i in range(25)]\n", "X = (y + np.random.randn(25)).reshape(-1, 1)\n", "\n", - "cv5_idx = list(StratifiedKFold(y, n_folds=5, shuffle=False, random_state=0))\n", - "cross_val_score(LogisticRegression(random_state=123), X, y, cv=cv5_idx)" + "if Version(sklearn_version) < '0.18':\n", + " cv5_idx = list(StratifiedKFold(y, n_folds=5, shuffle=False, random_state=0))\n", + "\n", + "else:\n", + " cv5_idx = list(StratifiedKFold(n_splits=5, shuffle=False, random_state=0).split(X, y))\n", + " \n", + "cross_val_score(LogisticRegression(random_state=123), X, y, cv=cv5_idx)\n" ] }, { @@ -1109,10 +1092,8 @@ }, { "cell_type": "code", - "execution_count": 39, - "metadata": { - "collapsed": false - }, + "execution_count": 38, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1135,13 +1116,19 @@ "name": "stderr", "output_type": "stream", "text": [ + "[Parallel(n_jobs=1)]: Done 1 out of 1 | elapsed: 0.0s remaining: 0.0s\n", + "[Parallel(n_jobs=1)]: Done 2 out of 2 | elapsed: 0.0s remaining: 0.0s\n", "[Parallel(n_jobs=1)]: Done 5 out of 5 | elapsed: 0.0s finished\n" ] } ], "source": [ - "from sklearn.grid_search import GridSearchCV\n", - "gs = GridSearchCV(LogisticRegression(), {}, cv=cv5_idx, verbose=3).fit(X, y) " + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.grid_search import GridSearchCV\n", + "else:\n", + " from sklearn.model_selection import GridSearchCV\n", + "\n", + "gs = GridSearchCV(LogisticRegression(), {}, cv=cv5_idx, verbose=3).fit(X, y) \n" ] }, { @@ -1160,10 +1147,8 @@ }, { "cell_type": "code", - "execution_count": 40, - "metadata": { - "collapsed": false - }, + "execution_count": 39, + "metadata": {}, "outputs": [ { "data": { @@ -1171,7 +1156,7 @@ "0.47999999999999998" ] }, - "execution_count": 40, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -1189,10 +1174,8 @@ }, { "cell_type": "code", - "execution_count": 41, - "metadata": { - "collapsed": false - }, + "execution_count": 40, + "metadata": {}, "outputs": [ { "data": { @@ -1200,7 +1183,7 @@ "0.47999999999999998" ] }, - "execution_count": 41, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -1238,7 +1221,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 48, "metadata": { "collapsed": true }, @@ -1267,10 +1250,8 @@ }, { "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, + "execution_count": 49, + "metadata": {}, "outputs": [ { "data": { @@ -1279,7 +1260,7 @@ " 1)" ] }, - "execution_count": 33, + "execution_count": 49, "metadata": {}, "output_type": "execute_result" } @@ -1290,10 +1271,8 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": { - "collapsed": false - }, + "execution_count": 50, + "metadata": {}, "outputs": [], "source": [ "def get_minibatch(doc_stream, size):\n", @@ -1310,10 +1289,8 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 51, + "metadata": {}, "outputs": [], "source": [ "from sklearn.feature_extraction.text import HashingVectorizer\n", @@ -1330,10 +1307,8 @@ }, { "cell_type": "code", - "execution_count": 36, - "metadata": { - "collapsed": false - }, + "execution_count": 52, + "metadata": {}, "outputs": [ { "name": "stderr", @@ -1341,7 +1316,7 @@ "text": [ "0% 100%\n", "[##############################] | ETA: 00:00:00\n", - "Total time elapsed: 00:00:33\n" + "Total time elapsed: 00:00:44\n" ] } ], @@ -1361,16 +1336,14 @@ }, { "cell_type": "code", - "execution_count": 37, - "metadata": { - "collapsed": false - }, + "execution_count": 53, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Accuracy: 0.868\n" + "Accuracy: 0.867\n" ] } ], @@ -1382,10 +1355,8 @@ }, { "cell_type": "code", - "execution_count": 38, - "metadata": { - "collapsed": false - }, + "execution_count": 54, + "metadata": {}, "outputs": [], "source": [ "clf = clf.partial_fit(X_test, y_test)" @@ -1423,9 +1394,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch09/ch09.ipynb b/code/ch09/ch09.ipynb index 4a10c1e8..2b9cb875 100644 --- a/code/ch09/ch09.ipynb +++ b/code/ch09/ch09.ipynb @@ -35,30 +35,29 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sebastian Raschka \n", - "Last updated: 08/20/2015 \n", + "last updated: 2016-09-29 \n", "\n", - "CPython 3.4.3\n", - "IPython 3.2.1\n", + "CPython 3.5.2\n", + "IPython 5.1.0\n", "\n", - "numpy 1.9.2\n", - "pandas 0.16.2\n", - "matplotlib 1.4.3\n", - "nltk 3.0.4\n" + "numpy 1.11.1\n", + "pandas 0.18.1\n", + "matplotlib 1.5.1\n", + "nltk 3.2.1\n", + "sklearn 0.18\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,nltk" + "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,nltk,sklearn" ] }, { @@ -148,7 +147,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": { "collapsed": true }, @@ -175,15 +174,14 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": true - }, + "execution_count": 3, + "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import re\n", "from nltk.corpus import stopwords\n", + "from nltk.stem import PorterStemmer\n", "\n", "stop = stopwords.words('english')\n", "porter = PorterStemmer()\n", @@ -205,10 +203,8 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { @@ -217,7 +213,7 @@ " 1)" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -267,10 +263,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [], "source": [ "def get_minibatch(doc_stream, size):\n", @@ -287,10 +281,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [], "source": [ "from sklearn.feature_extraction.text import HashingVectorizer\n", @@ -307,18 +299,16 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "0% 100%\n", - "[##############################] | ETA[sec]: 0.000 \n", - "Total time elapsed: 59.019 sec\n" + "[##############################] | ETA: 00:00:00\n", + "Total time elapsed: 00:00:41\n" ] } ], @@ -338,16 +328,14 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Accuracy: 0.868\n" + "Accuracy: 0.867\n" ] } ], @@ -359,10 +347,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [], "source": [ "clf = clf.partial_fit(X_test, y_test)" @@ -394,10 +380,8 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [], "source": [ "import pickle\n", @@ -420,10 +404,8 @@ }, { "cell_type": "code", - "execution_count": 1, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -477,7 +459,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 12, "metadata": { "collapsed": true }, @@ -489,10 +471,8 @@ }, { "cell_type": "code", - "execution_count": 2, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [], "source": [ "import pickle\n", @@ -505,17 +485,15 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Prediction: positive\n", - "Probability: 91.56%\n" + "Probability: 82.52%\n" ] } ], @@ -553,13 +531,15 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [], "source": [ "import sqlite3\n", + "import os\n", + "\n", + "if os.path.exists('reviews.sqlite'):\n", + " os.remove('reviews.sqlite')\n", "\n", "conn = sqlite3.connect('reviews.sqlite')\n", "c = conn.cursor()\n", @@ -577,10 +557,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [], "source": [ "conn = sqlite3.connect('reviews.sqlite')\n", @@ -594,16 +572,14 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[('I love this movie', 1, '2015-07-15 01:25:15'), ('I disliked this movie', 0, '2015-07-15 01:25:15')]\n" + "[('I love this movie', 1, '2016-09-30 01:31:01'), ('I disliked this movie', 0, '2016-09-30 01:31:01')]\n" ] } ], @@ -613,10 +589,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "data": { @@ -625,7 +599,7 @@ "" ] }, - "execution_count": 3, + "execution_count": 18, "metadata": { "image/png": { "width": 700 @@ -635,7 +609,7 @@ } ], "source": [ - "Image(filename='./images/09_01.png', width=700) " + "Image(filename='../images/09_01.png', width=700) " ] }, { @@ -670,7 +644,67 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "..." + "Directory structure:\n", + "\n", + " 1st_flask_app_1/\n", + " app.py\n", + " templates/\n", + " first_app.html\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "from flask import Flask, render_template\r\n", + "\r\n", + "app = Flask(__name__)\r\n", + "\r\n", + "@app.route('/')\r\n", + "def index():\r\n", + " return render_template('first_app.html')\r\n", + "\r\n", + "if __name__ == '__main__':\r\n", + " app.run(debug=True)" + ] + } + ], + "source": [ + "!cat 1st_flask_app_1/app.py" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r\n", + "\r\n", + " \r\n", + " First app\r\n", + " \r\n", + " \r\n", + "\r\n", + "
\r\n", + "\tHi, this is my first Flask web app!\r\n", + "
\r\n", + "\r\n", + " \r\n", + "" + ] + } + ], + "source": [ + "!cat 1st_flask_app_1/templates/first_app.html" ] }, { @@ -682,10 +716,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "data": { @@ -694,7 +726,7 @@ "" ] }, - "execution_count": 6, + "execution_count": 19, "metadata": { "image/png": { "width": 400 @@ -704,15 +736,13 @@ } ], "source": [ - "Image(filename='./images/09_02.png', width=400) " + "Image(filename='../images/09_02.png', width=400) " ] }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 20, + "metadata": {}, "outputs": [ { "data": { @@ -721,7 +751,7 @@ "" ] }, - "execution_count": 7, + "execution_count": 20, "metadata": { "image/png": { "width": 400 @@ -731,7 +761,91 @@ } ], "source": [ - "Image(filename='./images/09_03.png', width=400) " + "Image(filename='../images/09_03.png', width=400) " + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Directory structure:\n", + " \n", + " 1st_flask_app_2/\n", + " app.py\n", + " static/\n", + " style.css\n", + " templates/\n", + " _formhelpers.html\n", + " first_app.html\n", + " hello.html" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "from flask import Flask, render_template, request\r\n", + "from wtforms import Form, TextAreaField, validators\r\n", + "\r\n", + "app = Flask(__name__)\r\n", + "\r\n", + "class HelloForm(Form):\r\n", + " sayhello = TextAreaField('',[validators.DataRequired()])\r\n", + "\r\n", + "@app.route('/')\r\n", + "def index():\r\n", + " form = HelloForm(request.form)\r\n", + " return render_template('first_app.html', form=form)\r\n", + "\r\n", + "@app.route('/hello', methods=['POST'])\r\n", + "def hello():\r\n", + " form = HelloForm(request.form)\r\n", + " if request.method == 'POST' and form.validate():\r\n", + " name = request.form['sayhello']\r\n", + " return render_template('hello.html', name=name)\r\n", + " return render_template('first_app.html', form=form)\r\n", + "\r\n", + "if __name__ == '__main__':\r\n", + " app.run(debug=True)" + ] + } + ], + "source": [ + "!cat 1st_flask_app_2/app.py" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{% macro render_field(field) %}\r\n", + "
{{ field.label }}\r\n", + "
{{ field(**kwargs)|safe }}\r\n", + " {% if field.errors %}\r\n", + "
    \r\n", + " {% for error in field.errors %}\r\n", + "
  • {{ error }}
    • \r\n", + " {% endfor %}\r\n", + "
\r\n", + " {% endif %}\r\n", + "
\r\n", + " \r\n", + "{% endmacro %}\r\n" + ] + } + ], + "source": [ + "!cat 1st_flask_app_2/templates/_formhelpers.html" ] }, { @@ -751,10 +865,8 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "data": { @@ -763,7 +875,7 @@ "" ] }, - "execution_count": 8, + "execution_count": 21, "metadata": { "image/png": { "width": 400 @@ -773,15 +885,13 @@ } ], "source": [ - "Image(filename='./images/09_04.png', width=400) " + "Image(filename='../images/09_04.png', width=400) " ] }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { @@ -790,7 +900,7 @@ "" ] }, - "execution_count": 9, + "execution_count": 22, "metadata": { "image/png": { "width": 400 @@ -800,15 +910,13 @@ } ], "source": [ - "Image(filename='./images/09_05.png', width=400) " + "Image(filename='../images/09_05.png', width=400) " ] }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "data": { @@ -817,7 +925,7 @@ "" ] }, - "execution_count": 10, + "execution_count": 23, "metadata": { "image/png": { "width": 400 @@ -827,15 +935,13 @@ } ], "source": [ - "Image(filename='./images/09_06.png', width=400) " + "Image(filename='../images/09_06.png', width=400) " ] }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 24, + "metadata": {}, "outputs": [ { "data": { @@ -844,7 +950,7 @@ "" ] }, - "execution_count": 12, + "execution_count": 24, "metadata": { "image/png": { "width": 200 @@ -854,7 +960,244 @@ } ], "source": [ - "Image(filename='./images/09_07.png', width=200) " + "Image(filename='../images/09_07.png', width=200) " + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "from flask import Flask, render_template, request\r\n", + "from wtforms import Form, TextAreaField, validators\r\n", + "import pickle\r\n", + "import sqlite3\r\n", + "import os\r\n", + "import numpy as np\r\n", + "\r\n", + "# import HashingVectorizer from local dir\r\n", + "from vectorizer import vect\r\n", + "\r\n", + "app = Flask(__name__)\r\n", + "\r\n", + "######## Preparing the Classifier\r\n", + "cur_dir = os.path.dirname(__file__)\r\n", + "clf = pickle.load(open(os.path.join(cur_dir,\r\n", + " 'pkl_objects',\r\n", + " 'classifier.pkl'), 'rb'))\r\n", + "db = os.path.join(cur_dir, 'reviews.sqlite')\r\n", + "\r\n", + "def classify(document):\r\n", + " label = {0: 'negative', 1: 'positive'}\r\n", + " X = vect.transform([document])\r\n", + " y = clf.predict(X)[0]\r\n", + " proba = np.max(clf.predict_proba(X))\r\n", + " return label[y], proba\r\n", + "\r\n", + "def train(document, y):\r\n", + " X = vect.transform([document])\r\n", + " clf.partial_fit(X, [y])\r\n", + "\r\n", + "def sqlite_entry(path, document, y):\r\n", + " conn = sqlite3.connect(path)\r\n", + " c = conn.cursor()\r\n", + " c.execute(\"INSERT INTO review_db (review, sentiment, date)\"\\\r\n", + " \" VALUES (?, ?, DATETIME('now'))\", (document, y))\r\n", + " conn.commit()\r\n", + " conn.close()\r\n", + "\r\n", + "######## Flask\r\n", + "class ReviewForm(Form):\r\n", + " moviereview = TextAreaField('',\r\n", + " [validators.DataRequired(),\r\n", + " validators.length(min=15)])\r\n", + "\r\n", + "@app.route('/')\r\n", + "def index():\r\n", + " form = ReviewForm(request.form)\r\n", + " return render_template('reviewform.html', form=form)\r\n", + "\r\n", + "@app.route('/results', methods=['POST'])\r\n", + "def results():\r\n", + " form = ReviewForm(request.form)\r\n", + " if request.method == 'POST' and form.validate():\r\n", + " review = request.form['moviereview']\r\n", + " y, proba = classify(review)\r\n", + " return render_template('results.html',\r\n", + " content=review,\r\n", + " prediction=y,\r\n", + " probability=round(proba*100, 2))\r\n", + " return render_template('reviewform.html', form=form)\r\n", + "\r\n", + "@app.route('/thanks', methods=['POST'])\r\n", + "def feedback():\r\n", + " feedback = request.form['feedback_button']\r\n", + " review = request.form['review']\r\n", + " prediction = request.form['prediction']\r\n", + "\r\n", + " inv_label = {'negative': 0, 'positive': 1}\r\n", + " y = inv_label[prediction]\r\n", + " if feedback == 'Incorrect':\r\n", + " y = int(not(y))\r\n", + " train(review, y)\r\n", + " sqlite_entry(db, review, y)\r\n", + " return render_template('thanks.html')\r\n", + "\r\n", + "if __name__ == '__main__':\r\n", + " app.run(debug=True)\r\n" + ] + } + ], + "source": [ + "!cat ./movieclassifier/app.py" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r\n", + "\r\n", + " \r\n", + " Movie Classification\r\n", + "\t\r\n", + " \r\n", + " \r\n", + "\r\n", + "

Please enter your movie review:

\r\n", + "\r\n", + "{% from \"_formhelpers.html\" import render_field %}\r\n", + "\r\n", + "
\r\n", + "
\r\n", + "\t{{ render_field(form.moviereview, cols='30', rows='10') }}\r\n", + "
\r\n", + "
\r\n", + "\t \r\n", + "
\r\n", + "
\r\n", + "\r\n", + " \r\n", + "" + ] + } + ], + "source": [ + "!cat ./movieclassifier/templates/reviewform.html" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r\n", + "\r\n", + " \r\n", + " Movie Classification\r\n", + "\t\r\n", + " \r\n", + " \r\n", + "\r\n", + "

Your movie review:

\r\n", + "
{{ content }}
\r\n", + "\r\n", + "

Prediction:

\r\n", + "
This movie review is {{ prediction }}\r\n", + "\t (probability: {{ probability }}%).
\r\n", + "\r\n", + "
\r\n", + "\t
\r\n", + "\t \r\n", + "\t\t\r\n", + "\t\t\r\n", + "\t\t\r\n", + "\t
\r\n", + "
\r\n", + "\r\n", + "
\r\n", + "\t
\r\n", + "\t \r\n", + "\t
\r\n", + "
\r\n", + "\r\n", + " \r\n", + "\r\n" + ] + } + ], + "source": [ + "!cat ./movieclassifier/templates/results.html" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "body{\r\n", + "\twidth:600px;\r\n", + "}\r\n", + "\r\n", + ".button{\r\n", + "\tpadding-top: 20px;\r\n", + "}\r\n" + ] + } + ], + "source": [ + "!cat ./movieclassifier/static/style.css" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r\n", + "\r\n", + " \r\n", + " Movie Classification\r\n", + "\t\r\n", + " \r\n", + " \r\n", + "\r\n", + "

Thank you for your feedback!

\r\n", + "\r\n", + "
\r\n", + "\t
\r\n", + "\t \r\n", + "\t
\r\n", + "
\r\n", + "\r\n", + " \r\n", + "" + ] + } + ], + "source": [ + "!cat ./movieclassifier/templates/thanks.html" ] }, { @@ -874,10 +1217,8 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 25, + "metadata": {}, "outputs": [ { "data": { @@ -886,7 +1227,7 @@ "" ] }, - "execution_count": 14, + "execution_count": 25, "metadata": { "image/png": { "width": 600 @@ -896,7 +1237,7 @@ } ], "source": [ - "Image(filename='./images/09_08.png', width=600) " + "Image(filename='../images/09_08.png', width=600) " ] }, { @@ -921,18 +1262,6 @@ "Change current directory to `movieclassifier`:" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ - "import os\n", - "os.chdir('movieclassifier')" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -942,10 +1271,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 26, + "metadata": {}, "outputs": [], "source": [ "import pickle\n", @@ -985,10 +1312,8 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 27, + "metadata": {}, "outputs": [], "source": [ "cur_dir = '.'\n", @@ -1013,6 +1338,66 @@ "# , protocol=4)" ] }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "import pickle\r\n", + "import sqlite3\r\n", + "import numpy as np\r\n", + "import os\r\n", + "\r\n", + "# import HashingVectorizer from local dir\r\n", + "from vectorizer import vect\r\n", + "\r\n", + "def update_model(db_path, model, batch_size=10000):\r\n", + "\r\n", + " conn = sqlite3.connect(db_path)\r\n", + " c = conn.cursor()\r\n", + " c.execute('SELECT * from review_db')\r\n", + "\r\n", + " results = c.fetchmany(batch_size)\r\n", + " while results:\r\n", + " data = np.array(results)\r\n", + " X = data[:, 0]\r\n", + " y = data[:, 1].astype(int)\r\n", + "\r\n", + " classes = np.array([0, 1])\r\n", + " X_train = vect.transform(X)\r\n", + " model.partial_fit(X_train, y, classes=classes)\r\n", + " results = c.fetchmany(batch_size)\r\n", + "\r\n", + " conn.close()\r\n", + " return model\r\n", + "\r\n", + "cur_dir = os.path.dirname(__file__)\r\n", + "\r\n", + "clf = pickle.load(open(os.path.join(cur_dir,\r\n", + " 'pkl_objects',\r\n", + " 'classifier.pkl'), 'rb'))\r\n", + "db = os.path.join(cur_dir, 'reviews.sqlite')\r\n", + "\r\n", + "clf = update_model(db_path=db, model=clf, batch_size=10000)\r\n", + "\r\n", + "# Uncomment the following lines if you are sure that\r\n", + "# you want to update your classifier.pkl file\r\n", + "# permanently.\r\n", + "\r\n", + "# pickle.dump(clf, open(os.path.join(cur_dir,\r\n", + "# 'pkl_objects', 'classifier.pkl'), 'wb')\r\n", + "# , protocol=4)\r\n" + ] + } + ], + "source": [ + "!cat ./movieclassifier_with_update/update.py" + ] + }, { "cell_type": "markdown", "metadata": { @@ -1035,6 +1420,7 @@ "metadata": {}, "source": [ "
\n", + "...\n", "
" ] } @@ -1055,9 +1441,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.0" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch09/movieclassifier/pkl_objects/classifier.pkl b/code/ch09/movieclassifier/pkl_objects/classifier.pkl index 28aca72a..844975ad 100644 Binary files a/code/ch09/movieclassifier/pkl_objects/classifier.pkl and b/code/ch09/movieclassifier/pkl_objects/classifier.pkl differ diff --git a/code/ch09/movieclassifier/pkl_objects/stopwords.pkl b/code/ch09/movieclassifier/pkl_objects/stopwords.pkl index 91be340d..f1b186fa 100644 Binary files a/code/ch09/movieclassifier/pkl_objects/stopwords.pkl and b/code/ch09/movieclassifier/pkl_objects/stopwords.pkl differ diff --git a/code/ch09/movieclassifier/reviews.sqlite b/code/ch09/movieclassifier/reviews.sqlite index e72271b2..5eb25271 100644 Binary files a/code/ch09/movieclassifier/reviews.sqlite and b/code/ch09/movieclassifier/reviews.sqlite differ diff --git a/code/ch09/movieclassifier/vectorizer.py b/code/ch09/movieclassifier/vectorizer.py index 00d6e745..a4017c20 100644 --- a/code/ch09/movieclassifier/vectorizer.py +++ b/code/ch09/movieclassifier/vectorizer.py @@ -5,8 +5,8 @@ cur_dir = os.path.dirname(__file__) stop = pickle.load(open( - os.path.join(cur_dir, - 'pkl_objects', + os.path.join(cur_dir, + 'pkl_objects', 'stopwords.pkl'), 'rb')) def tokenizer(text): @@ -21,4 +21,4 @@ def tokenizer(text): vect = HashingVectorizer(decode_error='ignore', n_features=2**21, preprocessor=None, - tokenizer=tokenizer) + tokenizer=tokenizer) \ No newline at end of file diff --git a/code/ch10/ch10.ipynb b/code/ch10/ch10.ipynb index f9578e66..bbef1011 100644 --- a/code/ch10/ch10.ipynb +++ b/code/ch10/ch10.ipynb @@ -44,22 +44,22 @@ "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-04-12 \n", + "last updated: 2016-09-29 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.0.3\n", + "CPython 3.5.2\n", + "IPython 5.1.0\n", "\n", - "numpy 1.10.4\n", - "pandas 0.17.1\n", - "matplotlib 1.5.0\n", - "scikit-learn 0.17.1\n", - "seaborn 0.6.0\n" + "numpy 1.11.1\n", + "pandas 0.18.1\n", + "matplotlib 1.5.1\n", + "sklearn 0.18\n", + "seaborn 0.7.0\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scikit-learn,seaborn" + "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,sklearn,seaborn" ] }, { @@ -117,24 +117,27 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "from IPython.display import Image" + "from IPython.display import Image\n", + "%matplotlib inline" ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ - "%matplotlib inline" + "# Added version check for recent scikit-learn 0.18 checks\n", + "from distutils.version import LooseVersion as Version\n", + "from sklearn import __version__ as sklearn_version" ] }, { @@ -146,7 +149,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": { "collapsed": false }, @@ -158,7 +161,7 @@ "" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": { "image/png": { "width": 500 @@ -217,7 +220,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": { "collapsed": false }, @@ -250,7 +253,7 @@ " \n", " 0\n", " 0.00632\n", - " 18\n", + " 18.0\n", " 2.31\n", " 0\n", " 0.538\n", @@ -258,7 +261,7 @@ " 65.2\n", " 4.0900\n", " 1\n", - " 296\n", + " 296.0\n", " 15.3\n", " 396.90\n", " 4.98\n", @@ -267,7 +270,7 @@ " \n", " 1\n", " 0.02731\n", - " 0\n", + " 0.0\n", " 7.07\n", " 0\n", " 0.469\n", @@ -275,7 +278,7 @@ " 78.9\n", " 4.9671\n", " 2\n", - " 242\n", + " 242.0\n", " 17.8\n", " 396.90\n", " 9.14\n", @@ -284,7 +287,7 @@ " \n", " 2\n", " 0.02729\n", - " 0\n", + " 0.0\n", " 7.07\n", " 0\n", " 0.469\n", @@ -292,7 +295,7 @@ " 61.1\n", " 4.9671\n", " 2\n", - " 242\n", + " 242.0\n", " 17.8\n", " 392.83\n", " 4.03\n", @@ -301,7 +304,7 @@ " \n", " 3\n", " 0.03237\n", - " 0\n", + " 0.0\n", " 2.18\n", " 0\n", " 0.458\n", @@ -309,7 +312,7 @@ " 45.8\n", " 6.0622\n", " 3\n", - " 222\n", + " 222.0\n", " 18.7\n", " 394.63\n", " 2.94\n", @@ -318,7 +321,7 @@ " \n", " 4\n", " 0.06905\n", - " 0\n", + " 0.0\n", " 2.18\n", " 0\n", " 0.458\n", @@ -326,7 +329,7 @@ " 54.2\n", " 6.0622\n", " 3\n", - " 222\n", + " 222.0\n", " 18.7\n", " 396.90\n", " 5.33\n", @@ -337,22 +340,22 @@ "" ], "text/plain": [ - " CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX PTRATIO \\\n", - "0 0.00632 18 2.31 0 0.538 6.575 65.2 4.0900 1 296 15.3 \n", - "1 0.02731 0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 \n", - "2 0.02729 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 \n", - "3 0.03237 0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 \n", - "4 0.06905 0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 \n", + " CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX \\\n", + "0 0.00632 18.0 2.31 0 0.538 6.575 65.2 4.0900 1 296.0 \n", + "1 0.02731 0.0 7.07 0 0.469 6.421 78.9 4.9671 2 242.0 \n", + "2 0.02729 0.0 7.07 0 0.469 7.185 61.1 4.9671 2 242.0 \n", + "3 0.03237 0.0 2.18 0 0.458 6.998 45.8 6.0622 3 222.0 \n", + "4 0.06905 0.0 2.18 0 0.458 7.147 54.2 6.0622 3 222.0 \n", "\n", - " B LSTAT MEDV \n", - "0 396.90 4.98 24.0 \n", - "1 396.90 9.14 21.6 \n", - "2 392.83 4.03 34.7 \n", - "3 394.63 2.94 33.4 \n", - "4 396.90 5.33 36.2 " + " PTRATIO B LSTAT MEDV \n", + "0 15.3 396.90 4.98 24.0 \n", + "1 17.8 396.90 9.14 21.6 \n", + "2 17.8 392.83 4.03 34.7 \n", + "3 18.7 394.63 2.94 33.4 \n", + "4 18.7 396.90 5.33 36.2 " ] }, - "execution_count": 7, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -420,7 +423,7 @@ " \n", " 0\n", " 0.00632\n", - " 18\n", + " 18.0\n", " 2.31\n", " 0\n", " 0.538\n", @@ -428,7 +431,7 @@ " 65.2\n", " 4.0900\n", " 1\n", - " 296\n", + " 296.0\n", " 15.3\n", " 396.90\n", " 4.98\n", @@ -437,7 +440,7 @@ " \n", " 1\n", " 0.02731\n", - " 0\n", + " 0.0\n", " 7.07\n", " 0\n", " 0.469\n", @@ -445,7 +448,7 @@ " 78.9\n", " 4.9671\n", " 2\n", - " 242\n", + " 242.0\n", " 17.8\n", " 396.90\n", " 9.14\n", @@ -454,7 +457,7 @@ " \n", " 2\n", " 0.02729\n", - " 0\n", + " 0.0\n", " 7.07\n", " 0\n", " 0.469\n", @@ -462,7 +465,7 @@ " 61.1\n", " 4.9671\n", " 2\n", - " 242\n", + " 242.0\n", " 17.8\n", " 392.83\n", " 4.03\n", @@ -471,7 +474,7 @@ " \n", " 3\n", " 0.03237\n", - " 0\n", + " 0.0\n", " 2.18\n", " 0\n", " 0.458\n", @@ -479,7 +482,7 @@ " 45.8\n", " 6.0622\n", " 3\n", - " 222\n", + " 222.0\n", " 18.7\n", " 394.63\n", " 2.94\n", @@ -488,7 +491,7 @@ " \n", " 4\n", " 0.06905\n", - " 0\n", + " 0.0\n", " 2.18\n", " 0\n", " 0.458\n", @@ -496,7 +499,7 @@ " 54.2\n", " 6.0622\n", " 3\n", - " 222\n", + " 222.0\n", " 18.7\n", " 396.90\n", " 5.33\n", @@ -507,19 +510,19 @@ "" ], "text/plain": [ - " CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX PTRATIO \\\n", - "0 0.00632 18 2.31 0 0.538 6.575 65.2 4.0900 1 296 15.3 \n", - "1 0.02731 0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 \n", - "2 0.02729 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 \n", - "3 0.03237 0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 \n", - "4 0.06905 0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 \n", + " CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX \\\n", + "0 0.00632 18.0 2.31 0 0.538 6.575 65.2 4.0900 1 296.0 \n", + "1 0.02731 0.0 7.07 0 0.469 6.421 78.9 4.9671 2 242.0 \n", + "2 0.02729 0.0 7.07 0 0.469 7.185 61.1 4.9671 2 242.0 \n", + "3 0.03237 0.0 2.18 0 0.458 6.998 45.8 6.0622 3 222.0 \n", + "4 0.06905 0.0 2.18 0 0.458 7.147 54.2 6.0622 3 222.0 \n", "\n", - " B LSTAT MEDV \n", - "0 396.90 4.98 24.0 \n", - "1 396.90 9.14 21.6 \n", - "2 392.83 4.03 34.7 \n", - "3 394.63 2.94 33.4 \n", - "4 396.90 5.33 36.2 " + " PTRATIO B LSTAT MEDV \n", + "0 15.3 396.90 4.98 24.0 \n", + "1 17.8 396.90 9.14 21.6 \n", + "2 17.8 392.83 4.03 34.7 \n", + "3 18.7 394.63 2.94 33.4 \n", + "4 18.7 396.90 5.33 36.2 " ] }, "execution_count": 6, @@ -554,26 +557,16 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "collapsed": false }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/sebastian/miniconda3/lib/python3.5/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n", - " warnings.warn(self.msg_depr % (key, alt_key))\n", - "/Users/sebastian/miniconda3/lib/python3.5/site-packages/matplotlib/__init__.py:892: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n", - " warnings.warn(self.msg_depr % (key, alt_key))\n" - ] - }, { "data": { - "image/png": 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h/WNVOFPWjG8/Ogfl9W3455kGXj+dGi3Ud+871IeUuGAkx7YIxk1iYmHX6DOv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\n1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O2Oj9Fe62iFXAoLCwkIsyoSjkfIpUtvwGg00msw09/XQ3pitMMzs6VDT1+/SRJyud5n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\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VnRff3Mdr72SRU1LvsFMol8s4ml87oFS4xP2B7XdPtbO9l5bEEhHi55CGmKmvISFCLQpR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\n", 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Kq5VS1FcYsfaWXHRc7EdVqRkSDvjRb8dH6D4TrbNuX5gZT7S2TnSfZvtMTDWddKnI66IY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H+Ocm9AJ3mUvLiCSnz/yNzTLmkYn7IUsAwj1uRpVHKwDHWqKYtPZ6sNh/e14dzV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FIpHgxRdfRGJiYpfaefLkSbz22mvYtGkTLl26hDVr1kAoFCItLQ1PP/10p+U5HA48+eST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\n+bjzzju7/R6JgUl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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -596,24 +589,16 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { "collapsed": false }, "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/sebastian/miniconda3/lib/python3.5/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n", - " warnings.warn(self.msg_depr % (key, alt_key))\n" - ] - }, { "data": { "image/png": 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8u95fy/5Pv6HPC+MA8AoNouPwgXw2cQYXo44Ru+8Q68a+TKcRg/AI8q+O5pSL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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -642,7 +627,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": { "collapsed": true }, @@ -685,7 +670,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": { "collapsed": true }, @@ -719,7 +704,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": { "collapsed": true }, @@ -731,22 +716,11 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 12, "metadata": { "collapsed": false }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/sebastian/miniconda3/lib/python3.5/site-packages/sklearn/preprocessing/data.py:583: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n", - "/Users/sebastian/miniconda3/lib/python3.5/site-packages/sklearn/preprocessing/data.py:646: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n" - ] - } - ], + "outputs": [], "source": [ "from sklearn.preprocessing import StandardScaler\n", "\n", @@ -754,12 +728,12 @@ "sc_x = StandardScaler()\n", "sc_y = StandardScaler()\n", "X_std = sc_x.fit_transform(X)\n", - "y_std = sc_y.fit_transform(y)" + "y_std = sc_y.fit_transform(y[:, np.newaxis]).flatten()" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 13, "metadata": { "collapsed": false }, @@ -767,10 +741,10 @@ { "data": { "text/plain": [ - "<__main__.LinearRegressionGD at 0x11a399e48>" + "<__main__.LinearRegressionGD at 0x118f523c8>" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -782,7 +756,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 14, "metadata": { "collapsed": false }, @@ -791,7 +765,7 @@ "data": { "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -809,7 +783,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": { "collapsed": true }, @@ -823,16 +797,16 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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Ridx9W9wGrW9jSxE+7JL414SKizsF9Q6mKhIopd7WWj9SOJ5oHheEawVvhHh7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\nuPh4Dh782rLtuPC1BCZOeI6FryU47dT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oURrCtYJXFVThhB0w9YM6orX+qpTyuVtLFFQg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\nWqtEtSC92Rpi38U9w1l4S3tPvAV9M96V+Wm5WjAT2DWVpRd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rN9hNWcEInbZH0n388ceY+cQTjkTZj997E5ufK/Iww5WVlUmWK3q4YBwUCgUS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\n+/jriotROGY4DMYE1FYflpyjI5bJYjopcpZZAP4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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -850,7 +824,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "metadata": { "collapsed": false }, @@ -871,7 +845,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "metadata": { "collapsed": false }, @@ -882,18 +856,10 @@ "text": [ "Price in $1000's: 10.840\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/sebastian/miniconda3/lib/python3.5/site-packages/sklearn/preprocessing/data.py:646: DeprecationWarning: Passing 1d arrays as data is deprecated in 0.17 and will raise ValueError in 0.19. Reshape your data either using X.reshape(-1, 1) if your data has a single feature or X.reshape(1, -1) if it contains a single sample.\n", - " warnings.warn(DEPRECATION_MSG_1D, DeprecationWarning)\n" - ] } ], "source": [ - "num_rooms_std = sc_x.transform([5.0]) \n", + "num_rooms_std = sc_x.transform(np.array([[5.0]]))\n", "price_std = lr.predict(num_rooms_std)\n", "print(\"Price in $1000's: %.3f\" % sc_y.inverse_transform(price_std))" ] @@ -915,7 +881,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "metadata": { "collapsed": false }, @@ -926,7 +892,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": { "collapsed": false }, @@ -950,16 +916,16 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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2CoixsbGseOdt+/2a3tLYKUlC1vqJUJfnflBKqZuAmcAdGEVdw4BdwDCt9f5i\naaFzeyR5UHjkzw9bb9dyTSt/Y9IYIsqVp/+oCQC8aX6Z8PAI+++2rLuomjV5duBAtm3bRlJKCgNG\nGxsKLkmZyKUL5/lL27Zs2fZfakfXp3Gr1mSsWWHMM3nw+fz5/FmvntMi2+hGTZzS1vPzXri+Fk9p\n70L4W0H3g/IVoDYCo7XWWxyO3QXM0FrfU6SWFoIEKBFIFpfqCo4f/ABPDxxEpWuq033wS9zezsTo\nHo84bSro+vumtWksm2EmPDyC8+fOgtYMGDPR6fHls5P54/cz1KhZh6urVaft8SMsPOJhu3Wg84Bn\n4NRx1q9dS+e4OLeNCzO3ZNh7k74Cj7fzbfNXQgSCvzcsrOgYnAC01l8rle/rC1EiOPYoWj3cjaUp\nk6hd7yYi69Rl6LBhHD+eRZ/hRobdrBcHEd24CVlHDpO5f0+e1825dIk+LxpVxhclJbg9HlmrNufP\n/sn5s39y+OABj9ewDedlpEykqbVqhDeyyFyUJr4C1E6l1EKMQrFnMNZBPQx8G+iGCVEcHNcgeaqV\n17FnXxaax3F/fG+q1Yhi5T9ngdY0aN6SnIsX2bh6BVm/HKJ1+478/MM+Fk+dYD9/0ZTxdHisl9NC\nXlsaOVwp0jrp6d7w+29ubXtuyiyWTJvE0BpR3N7OBEDG8kV0josjOzubjKlXAp6tp2Qb2vP2OsEY\n9pO1fqIk8BWg/g9jW/a/YASn34APABkHEMUikBP5jr2mfQd/dnu8elQte3BZ+9ocNr+/hqjrb6DD\nY73Y/P4ae89o4ZRxHP5hP+XKVwCMPZ3O/fE71WpEOaWJGz8rFiUlcH39Bhy8rKn2dG+3+6Z17kZE\nyqu0B1CKT9KW2QNU5s8/Y+o1APbvgW93sfLVadSLvtFpGM818AwbOsRp2O+x7j1o1qypUZZpSwYg\na/1EaPKVxaeVUp8D4Riljk4BX8lEkCgOgS7aaxsOq1YjChUWziKH4qxLUiYyNGWO/fcTx48QffMt\nnDl5ku0Zn9LnxbFuGw2Gh4ehtea2v5ho2fY+pg15ykjttnpj0ljCIyJ49K+dWfruWx7bVKNmbXrd\n3c4ITlanso6xaW0aC6eM5/7HelGtRpSxYaE1GWO5Qxagp0Xm3iqpz0p9RQKTCGm+Sh09BfwDo/7e\nH0AzYLRS6k2tteexBAFICq8/5Gc+xdP7XJD3PnP/HpbNMNPnxbFk7t/DoqQEKlasQO7Fi5w+kcWm\ntWnW7Lx1TP3SAAAgAElEQVQr+ywtNI9zm3s6efwYA0Ynkrl/DxtXr2DH5xmUr1CR8PBw3po+mWsi\naxBerhx/nDkNHoJT1erXgtacP33SaZhw8dQJKBXG4qkTKF+uHNGNmvBJ2jK3AJlXSSVPw36yQaEo\nCXwN8Q0A7tFa2ytHKKXKA18AEqC8kO06iofFYiG+Rw/7DrLxPXowcvhwp7JHeb33115zDatWr2CA\nQ/286EZNSF+xlEMH9rN8djKRtWpTv0lzOjzqvJvtoqQEvvxoPRUrX8WJo7/QsVdfe89mgLVY7Jvm\ncTS98y5OHT/GPg+liQDe37Kb9I3p1LbOdy1Jmcj5P/5g3cJ5VKp8FZdzc7nh5pvRl3M5dzqb5TOn\nEFmnboHeJ9f5JtmgUJQUvgJUOaASzqWNKgMyxJcHyaTyD18T+a47yC5Jmcir/5zn9b133Gvp119P\ncDwri6urVXe7b0T58tzQ0Kga3rFnX7ZuTHd7zvX1G9gDCtasVk89myqJo5ly/pzb+d80b8nBVR/b\nf3ec70pfsZSff9hHxauuQoWF0ei2VvbafN3iupK2arXTcKRrBQlXtmE/2aBQlDS+AtQk4L9KqR8w\nsviqAg2BFwLdMCF8Fe09cvSY27boy6ZP9ngtW6+27SNx7P7s3/QbYXzAvz5pjNOQ2pKUidSp14DG\nrVqz4e3F9gw+x7kk2/yULXEhfcVSMtamUTu6/pUb5uby6ujnPbZl3OvvkDpiMP2su+O6znf9+dtv\nhIWH08faC1w2w0zLpFT6j05k3YJU/v7yZKrViOKTtGWcyjpGzZpRzJ0/n7nz5+c5zCkbFIqSJs+F\nugBKqQigCUZw+g3Yo7XOKYa2eWpLicjPKEur9IM513bPvffS6uFuTotNP337DbKOZ9nf+8VJCTRr\n1pTTp0+jy1fizMmT3PlArFOF8LWvzaGutccUVfcGvrJ8yPk//yA3J4eqkTVAQ27OJc6d/ZOKFSvR\n9uHOTuenr1jKkZ/+x6WLFwmPiOBPDynjYMwzlS9fgchatcn8YS9hYeHUqF2HX385zFPjzIARrC7n\n5DJgTKLT69q6MZ3WHTqybkEqXZ4Zan9scXIim1avsO9BZcvacxzmLM3//5UEMh99hb8X6mINRruK\n1Koypqxs1xHsubbxY8c6FUN1HOqyDWe179aT6EZNeNM8jgfir2yT3rLtffYe0JmTJ4jrMBiA+eNH\nUKFSJapFXseZkyeIH2T0gpYkJzJg1ASq1YjilRHP2dPHl6RM5OL589zWzsTX6R95bOemlR9xqsVt\nmJIT+dfKd+jlMCTZb0SC9edETv+aRdMmt/BTpnvK+6msY1eCj0PWXsbaNLc9qBYsSJUh5hAR7H8j\nJZ2vLD6vZY+11mP835zSoyxs1xHsuTZbMVTbFwHHYqlz58+n38gEp7Zt3Zhu7/mkzZnOzi8/Y+Pq\nFYBi5T9nERFRjnIVKjBgdCLpK5YS94/BVKsRxZrXXgGlWPvaHAaMmciQlFdZkpLIbyezqVrtWhpk\nHeMzL8GpcctWVH9tDg9278O+7Vv5+9hJTm36JG0ZI159g9Mnsli3IJWvv/ySu9q2dRpSXDRlPJUq\nV7J/sMXExNhfc4sWzf36ngr/Cva/kZLOVw8qCxgEmDG22xAi4AoyJOL6RcCxMkR0G5PX804e/YVP\nVx3gyTFGIFg0ZTwXL17gmQnJtI/rztaN6WTu38PSlEn0HWFUf1iSMpEZw/7BA/GPc/LYUarViPJa\nnqjzgGfYuGo5A6y9pdQRg7l44bzb8+xrnMzjGDNqJACJCQnE9+hh30k3LEzx/HPPOc0z2Wrm2b6h\n23jqZUkyhCixtNZ5/gGWAQ/4el5x/DGaK0LFhg0bdOR1UXpw0mw9OGm2jrwuSm/YsCFo13Q8t9OA\nZ3Tlq6vYr1P56iq604Bn7Nds0ry5Hpw0W7/8+ju6zYMP6+vrN9SVr66iq1SrrqvVqKlNXeP11ddU\n04OTZuvVe4/o1XuPGOfWrK3LVaigNXj8s/r7Q3r13iO6UctW7udGRTm16aqq1+gq1a7V1SJr6MmT\nJ7u9lk5du+pOXbvqyZMn5/meOD7XdtzTMVH8AvFvpCSzfobn+zPf5xwU8BRQ0V8B0Zp0sRCoB5TH\n6J3tBhZjbIj4ndb6WX/dTwROIObavA2JOP7XW6/K2+60t93WkjGjRrJl2za2f7Sbhg0bsG//D2zd\nlM6+7Vtp1+lRdm/7mifHTgKMntKXGz4golw5t3u89ftv/PXCBbfjw8uVY8HVVei3fjUAvxz80e05\njRs35uHYWJKTE6kdXZ8O3Xry5Qdr7b0b2w64jll3tuN5DRN5Gk4uC0PMJUFZmY8OlPwkSZwHzgMo\npRoAl7XWB4twzz7ACa11X6VUNWAnsAMYo7XerJSap5TqorVeV4R7iGLi7w/C7Oxsoj0cK8xEc3Sj\nJmTtNeoaf2SxcOrUKQ4fOozp0R607tyDRUkJDBidyNaN6W7p6mtfm8Nvp07yprW4a6VzZ3l1oudp\n16rVryU8PBx1WbMkZSL68mUuXbjglr7e9JbGjB079soc0qnj9uAkE+mll3xZKDxfSRJjgeu11v+n\nlBqCUVniolJqjdY6uZD3TANWWn8OB3KAVlrrzdZjHwMPAhKgyhiLxcKub79l13ffA9jLBoWHh9Ok\n9V0+J5pdF/YumZpAeHgErTv3IBojSJge7cHG1SvoPGAg19dv4LEdmfv3cPpEFgPGTCRz/x6v65nW\n7D3CprVp9ioQryWOplz58lxf31hH9a+Vb7NxzQqqVLsWU9d4sg/sBpw/sCwWC08PHJRnD0kqj4uy\nymuAUkpFAfFAvFIqGngW6AxcBN5WSi3XWrvnw/qgtT5rvX4VjEA1Fpju8JTfMQrTijJm7vz59BuV\naN/W4tCBffYkhjfN41g1L5XHBg31eK4tOaJhwwZs/8gYZqt81dXEPzfcLZNvwOhEliQn0vTOuz0u\nxN205l0GjJnoNTA1vjaSjsPHwdo0p0W2FSpVsi8AXjbDzAPxj7M941NyLl7k+/98Se6li1gsFrcd\nen2VLpJhIlFW5dWDqocxR3Q3cDPwM9DG+tjVgAko1Nc4pdQNwBpgjtZ6hVIqxeHhKsBpb+dOmDDB\n/rPJZMJkMhWmCSKE3d7OxJrXXuFJh91nwfjQj6xV260H4bjWJBpjPVRubg7Vomp5vUft6Pps/+xT\nlApj3/atVK12LW9Ofpmw8HAGXLjgMTj9UqsOWzK2cce8VJbPTubChfM0u/Nubm9nIuW5p9yGCdct\nnMepX48T9w9jjdWSlIkkJCbag0tCYiKRdeqiwsJZmjLJfp6nHpIME4mSKCMjg4yMjEKf7zVAaa3/\no5TKBNoBMRh7Q30LpGBUkyhscKoJWIBntdabrIe/UUrdq7X+N/BXYKO38x0DlChdHIeyjv+c6fZ4\nbk4OmVsy3HoQ3raTUGHhbiWKTF3jWTbDTLtOj3Ls55/oaw0q32zOYPaLg/j9tzMe21bpqqsJP/sn\nHZITyXhvpb2ntNA8jsXJiZzKOuZ2zsnjx3jSZd3TugWpgBFUv/9+t70CxKKkBNYtnAeXLkoPSZQa\nrp2IxMTEAp3vK0miK9ARSNVaf6eUKgd8zZU5pMIYDVQDximlxmMUnh0KvGq9/h5gVRGuL0oox6Gs\nyzmX3IJL3brX29f/uMrcv4eU554CjHJFNlWrXcvKf84mPDyMSxcu2LP2Nq5aTlh4OACr5qXyTmoy\nkzxc964HH+bB7n146kQWG9es4MuP1rv1lBYlJZBz6ZLTbrkLzePIzc11u941VavSOS6OHTt2ulWA\nWJSUwOgRwyU4CWHla8PCC8D7Dr9fAjzvtJZPWuvnAU+D+6aiXFeUDo5FTbs9Fm9frHr50iVmTZ/u\n8Zw2MTFMmZpsTxN/PXE04RERqPBwOjzaw17e6PLlXDL37eGXgz9yba3aVK5S1es80z/7P0PqN1tJ\nevUNwKiHl3PxIufPnXV/stZUqFCB++K62+vytWjbju++3MzS5CvfGJcmJ6L1ZUy9BnjcwffamrWY\nlfoKMTExEqSEIB9p5qL0CuUilrGxsaxetdLevleSp3ht35Zt2+xDad9szqC8S7JCy6RU+o0Yz5KU\nieTmXGLA6ERqHzvCmNQUj9d7Lmk2i6dO4NKFC2yyVhy39YjqNWnGshlm+3MXmscRXS+a+x9/yq24\n64Cxk9i6/l22f7SaQ4cOU75Cee5+uCvt47qTfeyo85YZDns0SSkcIQwSoMqoYBWxLEoZI28c1059\nkrbMbQjuk7RltO7QkfLlK9BrxPg8t8FYkpLIyaQEqkVeR92bG7EoKYGw8HByL+dyTdUqHDn4I6au\nRs/ul4M/Ur58ef74488827dv7z56vTCGzP172LTmXXZ9/Tm//nKYDo/1sve4OvV/htvbmewBsaQI\n5S85ouTLV4BSSt2GsfW7vaKE1vrJQDVKBF4wilgGIiiazWZ27vyWb7/dReb+PR6TFU5lHWNRUgJ/\n/HYGPASnalddzRMvT4YTWWQfPcKFC+f58/czfL/lS3IuXaJCeDg3N7yZq66qTNQtt5J1+BAqLByl\nFH2Gj2PrpnT7gl4welUt2rZj+cwpNL6lMb1eGGPfbbf/qAkA9orq/Ucm2Lfs8JShGMqkUrcINJ/7\nQQEopXYAc4BDtmNaa0sA2+WtHTo/7RW+dY6LI7qNyWlYKnNLhtckhFC8p8VioVv3HvYt1hdNGW/f\n3baDwzYbSZcuMdRDodZXypVjZLnylCtfARSEhYVxe7v2NG9zj31X24hy5exBxZa+3m9UImtfm8NV\nVatSPaoWv58+SYPmLck6bPzziKp7Azs2pfP6/HnMnT+f6DYm+35Ojq/9g6WvU7NuNKeyjnHy2C/c\nfffdHnshodpLCcb/Q6Jk8/t+UFbHtNZvFLJNIgSVhuoEc+fPZ4BLJly6tarDoqQEyuXkcPas5+G3\n6pE1CI8ox4MPd2bj6hX2ILdshpkq1a+lunUNVeNWre1bvrfr8hjZB3azdf27nDqRdWV9U3IiHR7t\n6bSJIaeO2wOJt8W4v/5ymAqVKgNw4fwF2nhIjpBeiijL8hugflJKjQK+wUgLR2udHrBWiYALRnWC\n4giK1aNq0T6uu9d5phrXRdHrhTH0wehxbc/41C3ILUlOZOi0uSyaMt5pzZOtnl5UzZo82bmH/ZzM\n/XucUswdX5ftfU5ITGShS1JE87vuYdeXm+3Zh0lJ43n/ww+JqlnT3lNyHYrN3L+HpwcO4rbbWga9\nN1UavuSI0JbfAFUBaGz9A0aQkgBVwvmrOkF+hqBsz2l8S2O2rn+XqJo1ixwUnx040GlH3SUpE/nt\n1Em4pY7bcxNGjGNR2jJ6OWyXDrDIoaCrTbXrojh9IotTJ7LcqllkLF/k9vzoRk2IrhdN5pYM4Eqw\nd3xfEhMSSEg0NkKsHlWLwUmppM2Z7raQN33FUlq3Mdl7So6+2ZzhFDCD3ZuSEkwi0HwVi43Qxpbv\nzxRTe0QJk58hKNdSRMtnTiExIaHIH2a2HXUnms1U3LGT337/ze05u25pxmv9nuZN8zhq13IvfRQW\nFubU+1k2bRK169Rm1ZzpKOU+VH7mt9+89hy8vWYw3pdhQ4eQlJJCx559OX0iiyM//c/t+rYeIGDf\nnNB2r/QVS90yFIOdki4lmEQg+epBLQV6A/uwDu1h7KyrgZsC2C5RQuQnG9BfGYOeemqxsbHEPvSQ\nx+d3HvCMkbiwMZ0H4nuzcdVyt2E2U9d4svZ+S+aWDLKzs6lZM4pDPx+i/+hEt6E72xCf47DdkaPH\naHxLY7d7e3rNW7ZkcOONN9p7UZ36P+NWLcNWeNbGsZdy7sypAr1fQpR0vipJ9Lb+t37xNEeUBjt2\n7HSq2u0PZrOZ5OkzqB1dn8atWvP4E3058WuWx+d2HvCMkfjQqIlT4sL1NzWkcavWLEpK4NqatWjX\n6VGnDQNtyQyuJYiWz04mslZtuJxLYoJxvW3btjnV0svvcFvDhg2dMt/+t2cXy6ZPpmLFiuRcOM/p\nE1lsWpvmcT6nTu1aLJuWd1FZIUoTWagrisRtDyZrQVbHD+yiTqZbLBampkyzB4NmiaNZf/6c2/Nm\nDHqen26sx2ZrAsJC8zgy9+9h3/at/PzDPmpF1yPr8CE6dOvJjk3p9g0DY2Nj7bvW2jL2bKIbNWHH\npnQa17/RXs3CYrGQPH2GWyBz3cMpvkcPe6mmn3/YS/2bbuJybi6bNho1kjP373FKklg2bZLb/Jzr\n8OjuqQlkLF/Emd9+o2FDz/tZBVKopryL0kkClCgUxw+qYUOHsGBBKpWuqc7QlDnc3s5EdKMm9g/s\nok6mz50/n/6jE4m9734eadvC7fGfIyKYNmk67eO6Y+vqp69YSmTktXy6ajn3P9aLoz//xCN9nwau\nDNV5Wq/zYPc+zBl9Zc+p5TOnMGzoELZs2+a09Xzt6CuDCt9sziB9xVLOnTnl1HMMD4+gY08jMC+e\nOoGGre8h472VNLvrHpYkJ3LVVVe5JUm4riPylMW3afWKAvfc/EFS3kVxy3eAUkrdjLEv1LfAL7Ji\ntuxy/aCaZa2Y0OrhbtzezuTxnMJMptuC4I4dO1n/3nuen6Q1ve69l1Yuh385+CP169Wjy8BhHrd0\nX/nqNDrHxdl7AbZeXq8XxtCu06MsSU6kRYvmDBs6hFmpr9hLFcX37EXlypWp17wly2aYydy/x2Nm\n3dz58+kzfJzbZon9Roxn68Z0THHd2bx+dYHeD4B927fm2XMLpGBUHxFlW35LHQ0G4oBrgSVAQ2Bw\nANslQpinD6pP337DbbuJMaNGFvoetiC4MzyC648dcXt8akICo6x7g40fO9Yp3XzRlPE0v/sv7P7P\nV16vf811NYl2SOd27eWtXLEcgKcHDiKyTl2yjx1l8/tr6Ged07KVM9r8wVqPmXV5OX44k93bvsbU\nNd45SWJqAi1uvdVj4LQ5mnnQ63Vl+E2UNvntQfUE7gU+1VrPVkptDWCbyrxQ/6DJOn6cfSuWsnVj\nOg927wPAH3/8yf3xve1zOPfH92bLtm2FvseGqVM9JkGMbdKEe2fNYpTDexIbG8tLLwxj+vTJRNW9\nkWEz53N7OxOLkxNZnJRA+249PWbL2Xp7jkORrtux23qJi5IS6NCtp9NQ22fvrSQnJ8etjdnZ2Ywf\nO9bj3NySlImgod9II6i1bHsfaXOmc/LYL4SHR9Dq4W6A8/CZbQgV4NEunVk+c4r9urb5vOIYfpOF\nuaK45TdAhWGkltuG9S4Epjki1Mf5LRYL+/btp89wo7eUOmIwXM6ladOmRLtkzWVuOV7wG1y+DOHh\nzHI5nBsWxvPmmSyfOYV7XdqTkJjI99/vpk79BnTs2dceeKIbNaFZs6Zw6jhNb2ls3/bC1DXe41Ck\n4xeD/fv2EVmnrj0IDxhtLLJdNS+V9Hff4vzZP+nQrSdfWT5031jx+jr2HtnTAwdBufLUqdeArMOH\nMHWNdxrau72didMnsli3IJUuzw9164lt27bNKXvxgw/WMmzoED6yvhZbokRxDL/JwlxR3PIboN4B\n/g1EK6U+ArxMCIiiCvVxfk9zK9s/Wu3WYyjIt2tbYPA2z/Rc0mzax3WnvUMbHDPcbKnh1WpEOSU4\nLJs2icaNGwHYFwbbzolu1MSYP1qbRosWzTGbzU5zTT8f+pS/W7Pr5oweSrtOj5K5fy+Hf/zBnnVn\n24qjarVr2bhmBVWqXYupa7yRIYjxgf76/Hk8/kRfujw5CIDFSQlcf30dp3TxxUkJXHX11W6vOzs7\n2yl70bZV/fsffsiBAz/av8T07P04EeUiiG5jytf7XRSyMFcUp3wFKK31HKXURqAZsFdrvSuwzRIl\nSWRkZKG/XVssFr7u1o31f7oXdR05zsxnX39Bay/n2oK5Y2p4nfoNWD47mdxLF8nNzaF15x4AbnNN\ntl6X7cM/OTmRfiMTaB/XnZTnnuLvLtl1S5ITqVKlCj2HjbZvjBgWHu5Up8/UNZ6M91bS1GHhru1+\nE81mdu36jvbdegLwy5oVrJg9lT//+IMHuhvzZ671/Bo2bOCWEGHLFnT9ErNu4TynnpwMv4nSIL9J\nEk8DjbTWw5VS6Uqpt7TWRdr6XXgW6uP8ebWvwN+ujxwh9qGHcD1jzm23kV6vHtGVr/KY9u36fjzY\nvQ+zXhzkFDBc54wAJprN9jbOnT+f1taCr99szqB8hYrkpUWL5hw6dNj+u6eNEZfPTibnwnnCIyKc\nEh1s9+s3MoHsY0dZv2i+vXq6bV8o25DjugWp3HZbS6dg7+ho5kFatGjudrxOvQb0G5FA2pzpnDtz\nSobfRKmQ3yG+QcCd1p//hjHcJwEqAEJ9nN9v7fNQ5+5yRARDJ00nc0uG17RvxwWs2dnZZCQnYorr\nzrU1a9HlyUFuvQ1Hu3Z951bh4pvNGfYhPFsPJKruDW4bENoyEqdYj3vaGDEiPIwKFSt5THQA7EOK\nrtXTP0lbZl87xqnjTuugHL8MLE5KYNSI4cTExLglYNiSPk6fyCJzS0ZI/T8jRGHlN0DlWovGorW+\npJSSNVBlWJHmIVq0gO++czvcuf8/2PfNNo4mJzLypRc9pn17yrBr9XA3r3M4vxz80b6F+rIZZkxx\n3e3zV7YAGFmnLn1eHOuUUXf055+4tW07tm5M5/SJX4msXYcFb7zJ6/PnMWbUSBYsSOXcubMsTU60\n38s2JNfaYRsOwOl+8T17Ue26KLd2nso65rG8ket7sCrtXft7YDuenZ0Nl3PzLJEkREmV3wC1Tim1\nGfgP0ApYH7gmlW2hnsUHhUyD/+AD6NTJ/fju3ZjXrGGTQzLArJlTiLFu3ufp2o6JJN9szqBO/Qac\nPPaLW526utfXcdrewuhdGJmFTll2VrYeyLLpk2ndvqM96aLPi2OBK38XY8eOdXsfhg0dwoI33vT6\n8mNjY6lb93p++uknp7miheZxVL6qMlvXv+vx79nbe+CaEh+qPW4hiiK/SRKTlVIfYOwHtVRrvTOw\nzSq7Qj2Lr8AB9Nw5qFzZ/fizz8Ico3L3lm3bPFZHcPyvp0BoG56zBZAlUxPY/tFqIiMjnQrA2ra3\n8NRDsWXZ2SyfOYWXhj3PrJlTnHpXju2ytcMWJGzvSdtH4vJMVKhevTr3P/4U1WpEsea1V/h5/17u\nj+9NdKMmTmubCkoy60Rp5Ws/qKe01m8opZK4sgaqpVKqh9Z6TOCbJ0JNgQKoh3kmAPJRJSs7O9tr\nIGwTE8MU8zjqNrjZLYC41rLzNV/mbU4tJibGqXeVl4lms/09sQ0TekpUiIyMBIye2idpy+g/akLI\nfhERIhT46kEdsv73ByA3wG0RhH4WX7784x/w+uvux8+dg4ru2XKeXnPDhg28BsIt27Zxf3xv/vMv\ni8+m5NW7yGuo0lvvyvXvwmKxsGvXd/bEiLwSFRxfp6ckC19tEqKs8bUflO0ToKfWumMxtKfMK+4s\nvoJ+IOYZQL/7zkiCcPXxx+BlU0HArZyPrXp4XqIbNaFl2/t8pqB74lh9Iq+q4Pn5u5g7fz6muO4s\nm2G2H/NWh9DxetUrV3CbMxs2dEjA5h8l8IkSSWvt8w/wLtAZuAVohLEmKl/n5nHNNsAm688NgM3A\nZ8DcPM7Rwn82bNigI6+L0oOTZuvBSbN15HVResOGDT7Paduunb6hXn3d5u67jedfvqy1MXDn/KdV\nq0K3Y/LkyV7b5vj8TgOe0VWqVddt27Xz2XbHcxu1bKUHJ83Wq/ce0av3HjGu1bVrvtrrqFPXrnpw\n0mz98uvv6DYPPqwbtWylr6/fULdt1y5fbenUtavu1LWr/Wd/tMnTfQr69yxEIFg/w/MdJ/KbxRcF\nDHOMa0CHwgZFpdRw4AngD+uhmcAYrfVmpdQ8pVQXrfW6wl5f5E9BEzKc0rsxvvW3nDzZc++oALux\neNse3VvvJa8U9Pzey3VjwsJ6duBAHuveg/6jE2ndoaO9HFHG2jSfuwq7Dj/6qoJeWKGeeCOENz4D\nlFKqKvA3rfVZP973AMb2HbbFvndorTdbf/4YeBCQABViHD/ooj7P4NVfs8Cl4vimd95hVloaOFRS\nKKy85o+KmrnmWqFicVICq9LeLVQbR40YTlJSAtfXb0C7To+y+f01TmuubFyH2cA5S7FUzD8K4Ue+\nsvgGAy8COUqpwfrKnFSRaK3XKqWiHW/l8PPvwDX+uI/IW2E+ECNycri/U3uu+WGf8wMffIAlIqJQ\ncyjF+cHs2OOxVaiodl0UzZo1LXTAGzt2LO9/+CGnzl4g6/AhtzVX4J6eH9+jB+HhEfaq8Lb3KhDz\njxL4REmldB5DMUqpLwETUBV4S2v9V7/d2AhQy7XWbZVSh7TWN1iPdwYe0FoP8XCOTkhIsP9uMpkw\nmUz+alKZVJDJ8x9796bB8uVOx7LuvJOoLVsA6BwXR3Qbk30oydhyI8Pj1upFaUdRmc1mpy0svvxg\nbZGDgWsAsgUB2zVd35vRPR6hY8++hXqvCts+SZIQxS0jI4OMjAz774mJiWitvaw/cedriO+81voi\ncEIpVb5wTcyX7Uqpe7XW/wb+Cmz09sQJ1l1UxRVF+fDJ11DZxo1w//00cDi0qW5dLr7+OrF5ZOcV\nRHEuNh07diwxMTHGe3bquFtwyu/76fq8UK+hGErtEWWDayciMTHR+5M9yG+SBDgPw/nbS8DrSqly\nwB5gVQDvVaoEtDTS8eNQq5bzsauugsOHaV+tmtvT/TWUlJ8AUdCg7On5jqWCOsfFkXX8OH/+eZbM\nn3/GFNed6EZNvL6f3t53bz0gt63bf/rRLc28KMNu0kMSpZGvIb7jwKcYwamD9WcAtNa9A9469/bo\nvNpbFhVlWM2ry5fhkUeM9UuOtmyBO+/0fI6V4wdlm5gY+3qm/H5o+hoqy+9z8ntNxzJFGe+ttG/X\nsWyG2WEuyf39LMz77itJorBBpaDvhxDBopTy6xBfd4efA5MDK0LL/PkwyKXEz/Tp8OKL+TrdtT5d\nQYR+YagAABAzSURBVHt2+UmJLmjadF7Pd0w7d93f6ZO0ZbTu4L/16Z6G2fwRRCSNXJRWvipJfFZc\nDRGF47cMrZ074bbbnI/dey98+ilE+B4Jdu0dlIYPzVNZx7y+n6GSGWexWNixY2exbPcuRHEryByU\nCEFFLo30++/QoAH8+qvz8UOHoG7dfF3CU2+p8S2NifZxnuP5jsOCsxwqe3v64C9ocMjr+bbHXCuR\nL05KoFmzprzi5f0syPvuaX7IH3NG+a2iLkRJleccVKiROajC8fhhqDUMHAivveb85A8/hIcfLtD1\nPc3HbF3/LgcO/OhzXsTT/IljLT5v81j+SJJwfSzr+HHCIyKIjIz0W6KBt9c3K/WVIs8ZOb7v32zO\nsFdRf33+vBLVUxVlh7/noEQJ56l388nAZ7h90iTnJz7/PMya5bf7RtWsSWJCgs8ehrcyR+vXrs1z\nHqugadOBrEqRF0+vb8GCVL8Pf8p276I0kgBVyjl+QFY+fMgoT+QYnOrXN6qQe9pUMJ+8DaEV9YM/\n0PNYJT01O1TmwYQIFAlQZUB4Tg7tuz1E9e+/dX7g+++hadMiX78o82DB+pAN6PoxB55e37ChQ3zO\ns+VHcW/NIkRxkzmoUu6H/v25eckSp2O7XniBFjNmBKlF7rz1ZAK5vsfXOiZ/9q4ClSQhRElT0Dko\nCVCl1ebNRpq4gy/q1OGPN9/0W3mi4hCoD/K8ApQsfBUiMCRAlXUnTsB11zkfCw83yhZFRganTX7g\nz6w92+PeglBAqnMIIQocoMIC2RhRjC5fhkcfdQ9On38OOTklPjg9/kRfotuYiG5j4vEn+mKxeN/5\nJT/Pt83fZG7JINO6OaL0kIQILdKDKg0WLoS//935mNkMY8YEpz1+VtAeTVF7QDLEJ0RgyDqosuT7\n76F5c+djd95p9JrKlQtOm0oByY4TIjRIgCqJ/vwTmjQxyhE5+ukniM5vgaGSw5+ljfJL9k8SIvhk\niK+kef55SE11Pvbee9ClS3DaU0z8nSQhhCh+ksVXWn34obFHk6P/+z+YOzc47RFCiAKSOajS5tAh\nuPFG52O1a8P+/XD11cFpkxBCFANJMw9VOTnwl7+4B6edO+HIEQlOQohSTwJUKJo+3cjC++KLK8fm\nzze2yLj11uC1SwghipEM8YWSLVvgrrucjz3yCKxbB2HyXUIIUbZIgAoFp04Z80oXLjgfP34coqKC\n0yYhhAgy+VoeTFpD795w7bXOwWnTJuMxCU5CiDJMAlSwvP22MWy3fPmVY+PHG4HJZApas4QQIlTI\nEF9x27cPbrnF+ditt8J//gMVKgSnTUIIEYIkQBWXc+egZUv44Qfn4wcOQIMGwWmTEEKEMBniKw6j\nRkHlys7BKS3NGM6T4CSEEB6FTA9KKaWAfwItgfPAU1rr/wW3VUWUng6uNeCefBLeeANUvqt9CCFE\nmRQyAQroClTQWrdVSrUBZlqPlTxHj0KdOs7HqlWDzEyoWjU4bRJCiBImlIb4/gJsANBabwFigtuc\nQsjNhQcecA9O27YZa50kOAkhRL6FUg+qKnDG4fccpVSY1vqy45MmTJhg/9lkMmEKlZTsV1+FIUOc\nj6Wmuh8TQogyIiMjg4yMjEKfHzLbbSilZgBfaa1XWX//WWt9o8tzQm+7je3b4Y47nI898ABs2ADh\n4cFpkxBChKCSvN3GF8AjwCql1F3AriC3J29nzhi7154543z8yBGjbJEQQogiCaU5qLXABaXUF8AM\nYFiQ2+OZ1kYmXrVqzsHJYjEek+AkhBB+ETJDfPkR9CG+tDTo0cP52IgRkJwcnPYIIUQJUpKH+ELX\njz9Cw4bOxxo1MjYPrFgxOG0SQohSLpSG+ELPxYtGnTzX4LR3r1FTT4KTEEIEjASovNxwA+xyyNV4\n6y1jnqlx4+C1SQghyggJUHkZOND4b+/ecPky9OkT3PYIIUQZIkkSQgghikVBkySkByWEECIkSYAS\nQggRkiRACSGECEkSoIQQQoQkCVBCCCFCkgQoIYQQIUkClBBCiJAkAUoIIURIkgAlhBAiJEmAEkII\nEZIkQAkhhAhJEqCEEEKEJAlQQgghQpIEKCGEECFJApQQQoiQJAFKCCFESJIAJYQQIiRJgBJCCBGS\nJEAJIYQISRKghBBChKSgBCilVJxS6m2H39sopb5WSm1WSo0PRpuCJSMjI9hN8KvS9npAXlNJUNpe\nD5TO11RQxR6glFKzATOgHA7PB3pqrdsBbZRSLYu7XcFS2v4nLG2vB+Q1lQSl7fVA6XxNBRWMHtQX\nwCDbL0qpKkB5rfVP1kMW4IEgtEsIIUQICViAUko9qZTapZT61uG/d2itV7o8tSrwm8PvvwPXBKpd\nQgghSgaltS7+myp1H/CM1rq3tQf1tda6mfWxIUCE1nqmh/OKv7FCCCH8RmutfD/LEBHIhuSH1vp3\npdQFpVR94CcgFpjg5bn5fmFCCCFKtqAHKKuBwDsYQ47pWuutQW6PEEKIIAvKEJ8QQgjhiyzUFUII\nEZJCPkAppcKUUm8qpT5XSv1bKdU02G3yF6VUlFLqZ6VUo2C3xR+UUv9VSm20/nkz2O0pKqXUKKXU\nl0qprUqpAcFuT1EppfoppTZZ/36+UkqdVUpVDXa7ikIpFaGUelsp9YVS6rOS/m9JKVXe+nq+Ukpt\nUEo1CHabisJahGGT9ecG1mIMnyml5ubn/JAPUEAnQGut/wKMA6YEuT1+oZSKwFigfDbYbfEHpVQF\nAK11B+ufvwe7TUVhzTS9W2vdFjABNwS3RUWntV6itW6vte4A/Bd4Tmv9m6/zQtzDQLjW+h5gEiX/\n8+Fp4Het9d3AECBfH+ShSCk1HHgdqGA9NBMYo7W+DwhTSnXxdY2QD1Ba63XAP6y/1gNOBa81fjUd\nmAccCXZD/KQlcJVSyqKU+pdSqk2wG1REscB3Sqn3gPXAB0Fuj98opWKAplrrEt/LBfYDEUophbF+\n8mKQ21NUTYGPAbTW+4EmwW1OkRwA4hx+v0Nrvdn688fkoyBDqGTx5UlrfVkptRjoCjwW5OYUmVKq\nP5Cltf5EKTUm2O3xk7PANK31m0qpm4GPlVKNtNaXg92wQqoB3Ag8AtyEEaRuCWqL/Gc0kBjsRvjJ\nH0B9YC8QifH3VZLtwHgN65RSdwF1lFJKl8BsNq31WqVUtMMhx2VC+SrIEPI9KJv/b+/8Y60u6zj+\netco0tR0aWluaDWZribpLNoQkil4m5vxR4amIjeXzFzIhtx+DtvdKjbph239UOAOmhmhtopm+GsY\nFuSywkgQSiJWAgWDkrgI+O6Pz3Pk3Nu9B9u59j3n3s/rn/O95/t9nu/nOeee834+z3Pv+2P7BuAc\nYJGkN1QcTrPMBC4ra7PjgGWSTqs4pmbZDNwDYHsLsBs4vdKImmM3sMr24TKT7ZX05qqDahZJJwHn\n2H686liGiDnAz2yPJbL4ZZJeV3FMzbAE+JeknwNXAk+1ozgNQv1k9QRg77EatLxASbpW0qfKj73A\nEfoOtO2wPansBVxCzJiut72r6riapBNYCCDpDOIX8PlKI2qOJ4DL4eXxHEeIVrszEXi06iCGkD3A\nvnK8l1gVem114TTNRcCjticC9wHPVRzPUPIbSRPLcQewptHF0B5LfA8APZIeJ+KdbftgxTENJcNl\ndrSYeJ/WEBOIzjZe3sP2TyVdLOlJYmni5mEykx3L8PrS+xqwpGQco4BP2z5QcUzNsAXolvRZYr+9\nrf/YqB9zgbsljQI2EgLckPxH3SRJkqQlafklviRJkmRkkgKVJEmStCQpUEmSJElLkgKVJEmStCQp\nUEmSJElLkgKVJEmStCQpUEmlSJon6W9t/t//DSkO4q+Ky7akWyT9QdKHX43+/1ckzZf0rKTpknok\nrS/u6aslPS1pRrnudkmHJb21ru2pkl6UdL2kbknPS5pS3WiSqkmBSqrmo8C9wNVVB9KmTAOusr2i\n6kDqWGj7++V4bnG3/wAwCfhSed7As8BVde2mA9sAbH+eYpqajFzawUkiGaaUkhZ/JMqO3CNpJbDG\n9nnl/DeAR4A/AXeWZrsJW6ULgAXAQeAuwgbrE8TvtIFptveUujMXAjsJU9ErCKeLu4DRwAHg47b/\nWhfXDKKMw3GEUewC28uKd+JNtjdLugl4C7AUWA5sB8aU43cB7wFW2v5c6ba7ePn1EtZWuyV9EZhA\nWPN8xfb95R67gJOBqTX3imK6uaSM7yVgNvC+8joslvQR29vq4u8kHDDmE56It5Z7byGqAwjoKeN7\nTbn/inL/9WUMLxB2NFMJY88pwGml3aHS7pr6124A6ifBp5fXu8ZyQqBq7+0VwE/qztebiyYjkBSo\npEpuBBbZ3iLpIPAOYL2kCcCTRB2m2cAvgJm2N0nqBLqAh4HX2x4PUVwQ+KDtXknfBqZK2g+cYnt8\nEYfN5b53AF+3vUrSZELoru0X24m2OyS9k3AyX9ZgHGcTpQOOB7YSX8S9wJ+BmkDdVwRgFvAZSQ8D\nZ9ueWGpprZP0SLn2e6XMTD13AF+1vVLS+cBi2xdJuoYQ2G39rt9je5qkUwgxPt/2vyUtBGaVa3bZ\nvk7SG4GnJD1Wnl9n+1ZJDwL7bU+R1ENkQGcCvwLmEb5+JwGNBGpBse0ZAzxD32oEO4H9ks4iRPov\n5XVLEiAFKqkISW8ispRTJX0SOBG4hShwdgPxJf/jUmrlXOCbUfKHUUQWALFEVOPvwNIiSmOBXxK1\ndNYC2P6HpE3l2ncTItFFzNIPDRDi78rjdiLT+q8h1B0/Z/sFSYeAHbb3lTHW+4jVjDHXEpnCDuDC\nIgoiPotnDTCuGufW+rC9XtKZg8RSo9bH24ENtmuFMdcQmdARIjulxL6RmCAA/LY87iVEpXY8mvBc\n7AJWleeOVS5mnu2HJHUAX6avD6A5urw7inDDn3qM/pIRRO5BJVVxHZE9XW67AxgPXAY8TSyPzQQW\nlWs3Ectik4kvx1rxwJcAFGXLv0DsYdxIzMIFbADeX645mSjXAmFU2VX6mwUMtH8zkEllL0dLiFww\nyLgGW5Z6b3m8GPh9ieGxEsNk4AfEUubL4+rHM0TGgqRxhMA1otbHVuC8uhI1kwjx2ljX3wnEkl5N\nPBoZdF5JLMNeSph9dh0jjujQfhD4ETEBqeeB0ucE26tfSV/JyCEzqKQqOgmRAsD2AUn3EwKzArjU\n9tZy+mbgu5Jq+y8fA95W1/afkp4A1gGHiRIMZ9heKqmjnNtJFFU8BNwGfEvSaCIrmP0KY76ztNtG\n32UtD3Jc/9yHJM0hSkPMsL1P0iXFhft44IclkxlMHG4jnKDnEp/bzgb3O3rj2OuaD6yWdITY8+sq\n7e4u7vOjgdtLljnYWGrHvyYy1ReJCe6cRrfv93M3UXKho3auvHfbS1xJ0od0M0+GLZLGAuNsLy97\nMRuAMbYHWtJLhoAihjtsf2cI+uoB7rX9UPORJe1ILvElw5ntwNWS1hJ/sjwvxen/whxJ05vpQFI3\nuR814skMKkmSJGlJMoNKkiRJWpIUqCRJkqQlSYFKkiRJWpIUqCRJkqQlSYFKkiRJWpL/AFRNO5pa\npYR8AAAAAElFTkSuQmCC\n", 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LvbtRfcR+fZvNhvETJkAIC4dSo8Vttccw5r77POy48POfw/T995hz6iQscQmo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\nCkiMMlKc2UJag0hTlq30eGF3JJhutVp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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -984,7 +950,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": { "collapsed": false }, @@ -1028,16 +994,16 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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6J7L0Kzw6hHYKDwZ1zt1TW7XqEHK+SGWLwrvrGqOa+H5Qr+GuCRUDlUA/oJ9v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\n56ydHFGgHk/HqIka4Rf7oyUWxJocUNd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7nMf1PE45G2nDJL5kl1fc25Pk5Dgcjp9xuSpITu6F07kzpIavQssh3K2OjgPO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\ndSIFES8IsUSoEdRi4HGMllcQok5Iwwc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+DLoF9c/AUtuHATOBz9b55wPH2j4EOFDSfgOO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\nTkSuQmCC\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1047,13 +1013,22 @@ "source": [ "from sklearn.linear_model import RANSACRegressor\n", "\n", + "if Version(sklearn_version) < '0.18':\n", + " ransac = RANSACRegressor(LinearRegression(), \n", + " max_trials=100, \n", + " min_samples=50, \n", + " residual_metric=lambda x: np.sum(np.abs(x), axis=1), \n", + " residual_threshold=5.0, \n", + " random_state=0)\n", + "else:\n", + " ransac = RANSACRegressor(LinearRegression(), \n", + " max_trials=100, \n", + " min_samples=50, \n", + " loss='absolute_loss', \n", + " residual_threshold=5.0, \n", + " random_state=0)\n", + "\n", "\n", - "ransac = RANSACRegressor(LinearRegression(), \n", - " max_trials=100, \n", - " min_samples=50, \n", - " residual_metric=lambda x: np.sum(np.abs(x), axis=1), \n", - " residual_threshold=5.0, \n", - " random_state=0)\n", "ransac.fit(X, y)\n", "inlier_mask = ransac.inlier_mask_\n", "outlier_mask = np.logical_not(inlier_mask)\n", @@ -1076,7 +1051,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": { "collapsed": false }, @@ -1112,13 +1087,16 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": { "collapsed": false }, "outputs": [], "source": [ - "from sklearn.cross_validation import train_test_split\n", + "if Version(sklearn_version) < '0.18':\n", + " from sklearn.cross_validation import train_test_split\n", + "else:\n", + " from sklearn.model_selection import train_test_split\n", "\n", "X = df.iloc[:, :-1].values\n", "y = df['MEDV'].values\n", @@ -1129,7 +1107,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": { "collapsed": true }, @@ -1144,16 +1122,16 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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kMg5nMU7H12hufihoP6uXI7fbzbhxZ9Hd7QTms3UrjBs3kWXL7gN6X1Yczovo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\nyIRmbQ7tAwAAAABJRU5ErkJggg==\n", 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ejK7DYEl0vxVFyX/s32/K/b6GOlIKCr3filK4aKgjRVEUZUSgAqUoiqLkJcMiUMaYw40x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\nh4TtzEwE0RhzKtAOnCsiZxpjKoCXReQ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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1178,7 +1156,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": { "collapsed": false }, @@ -1196,7 +1174,6 @@ "from sklearn.metrics import r2_score\n", "from sklearn.metrics import mean_squared_error\n", "\n", - "\n", "print('MSE train: %.3f, test: %.3f' % (\n", " mean_squared_error(y_train, y_train_pred),\n", " mean_squared_error(y_test, y_test_pred)))\n", @@ -1222,7 +1199,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": { "collapsed": false }, @@ -1239,6 +1216,7 @@ ], "source": [ "from sklearn.linear_model import Lasso\n", + "\n", "lasso = Lasso(alpha=0.1)\n", "lasso.fit(X_train, y_train)\n", "y_train_pred = lasso.predict(X_train)\n", @@ -1248,7 +1226,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": { "collapsed": false }, @@ -1288,7 +1266,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": { "collapsed": false }, @@ -1306,7 +1284,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": { "collapsed": false }, @@ -1322,16 +1300,16 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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z8OCD8Pzz4Jsxy0SJpJkKlIgbnPznJANDB7L28Fo+euQjWlRs4bZ9DxrUk/Dw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\n1uzYAcWLezuViEjKaBRfFhV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Gp7WW2TaEWWkt9zHlRYa/UXfFilX4+LxNvnxuaH2L5ct/onXr1knPv/ZaF7ZsqUR8/H+B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\ndnZeREVVT3ykOra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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1361,7 +1339,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 34, "metadata": { "collapsed": false }, @@ -1373,7 +1351,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 35, "metadata": { "collapsed": false }, @@ -1413,16 +1391,16 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 36, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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ubq75ODU1lYiICIs+ycnJ5u/PnTtnnk05eo/ydOzYkZMnT9K1a1cAwsPDuXDh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\nUIqiKIorUQWlKIqiuBJVUIqiKIorUQWlKIqiuJKkKCgROV9Engk6niw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tLa1GawQHB1NQUKBdp6WlERERYdOnJi4pIQS9evVi+fLlvP/++zzzzDNaW0FB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\nPF4C31VRRhEPjX6ImefO5Ppjryc7LZvZG2bzi0W/SGh5saJzUIpylJK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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1496,16 +1474,16 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 37, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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f5ebmkpubazueMWNGqweuaQ1/dVo5Q2v9gNetN64XC5i01scbjv8PuEJrvd/u\nHOlxCa+1RuDyplfT2vbt68UDDySwZYtxfOGF5UyeXEznzt4NT3pTE9FZjUdfMidDlQxzhrZAzXFZ\nkzNSaZycscbXCKOU+hNwotb6HqVUBvBvYJBjj0sCl/CWv4YK7T/s/D0M6KuYmBj69evH/v3FPPts\nHS+9lEpFRRTx8fXccUcxt9xyiJgY93UWwfPWLfbnW79nzqqEOArlwCWJJaEvIIHLzfsStNYVPr4n\nBlgEZAH1wENa6w0O50jgEj5p6W/YvpZUam3WNU7WXl9hYTRz53Zl1ar2AGRnH2fq1AKGDHG+qNdk\nMlFXV+fTPa2p6t5sw2K/yaYzwZwjC3Q5K+G7YAeue7XWz/r6Pi+uK4FLBIw3FTECLS4ujurq6iZt\n+t//Epk9O4M9e8wAXHzxUSZOLKRLl9oW37M5VeudBaBgz5FJ4Ap9gUjOeAY4DyjDqFcIRr1CBZyg\nte7qc6s9kMAlAsVdTysmJoba2tqQ6YVZVVcrFi9O4W9/60JVlYnExDrGji3muusOEd3SvSB8YK3e\n4diTCvYcmQwVhr5ABC4F3Ku1nufkNelxibDm7kPWsadgNpupr6/3ulfS2vbti2HOnK7k5iYD0K+f\nsXHlySdXeninf5jNZqqrq5u1vq21e0CSnBHaApWc0VFrfcTJ1xO11s1fgen6fhK4REC42k05Nja2\nSYKC2Wx2uuNwsOXmJvHkk13Zv9+oyHHZZUeYMKGQTp18m+NyxllKPRgfPNHR0U2CuDfzZM56QBJo\nIksgelxxwHBgtdZaK6X6AwOAH7XWW5vZbk/tkcAlAsLVsFJLq2IEWmWl4tVXu7BoUQo1NSaSk2sZ\nP76IK688QpTPs9eetW/f3ml1+ri4OKqqqlwOr5pMJnr06NGqlehF6AtE4LoK6IiRCTgVOBeYiFG3\nMENrvag5DffQHglcImCc/bbf0ixDk8nktmfmOMzmLz//HMvs2Rl88YVRKmrQIGPjyoED3ae3+4ur\nHpqVs+1WJJki8rRq4FJKnQiMBf4LJADPAdOBAxjJGRcA87TWPzSv+S7bI4FLBJ19QHNVUNcZaw1C\nV8Nl9uWYHPf/8getYfXqZJ56qivFxTEopbnmmsP8+c9FtG/fesOcZrOZ6Oholz3VuLg4+vTp0+Tr\nErgiT6tua6K13gxsA/4FZGAUx50LHAKWAdv8HbSECBX2Oxk77oCslCImJgaTyYTZbCY1NdU2v5OZ\nmelynZPbTQpcAAAgAElEQVQ1qCUlJZGUlESfPn3IysoiMTERk8kfm5WDUnDRRWUsX76TW289iMkE\nb7/dmdGjf8VHH3WgNX4ntG6n4m7blygXY5be7MYsIk9LhwpjgZswAuDrWuvjSqlbgYPAKq11yxeQ\nNL2n9LhEyLH2wBx7X57WNBUWFjYaPnOVnNAavS+AnTvNzJqVwTffJAJw6qnlTJlygF/9qmWVQaKi\noqivr7cFGmugtlgsHDhwoEnihrtFy5KcEVmCugC5tUjgEqHM16EtT+cHpmqHYsWK9sydm87hw9FE\nRWluvPEQd99dTGKif4YP7Xc09sfwnwSztqtVhwqFEK2vpKSk1Rc5KwWjRh1lxYodXHfdIbSGJUtS\nGD26L598kuyX4cPjx4+Tn5+PxWLx6X0Wi4W8vDzy8vJs77UG8/LycsrLy5t1XRHeJHAJ4Ue+zskE\new7HuuYKIDm5nilTCnjzzZ848cQKiotjmDgxkzvu6EleXmyL76W1pqioyOkz19bWNgpO4DpAOQZz\nrTV79+6V4BVBWmWoUCl1NnBAa53Xksa5uLYMFYqQ5uswlrvzW3MLlaioKLp37+50XVp9Pbz/fkee\ney6N0tJooqPrGTOmhD/+8SDx8S379xcXF0dycjKlpaVN0v7t5/icDSnGxcURFRXlNDtR1ni1DQGd\n41JKTQX6ABUYmYZZWusXfWivVyRwiUjjbCsRb/bT8kQpxcCBA90GxyNHonj22TSWLesEQEZGNZMm\nFXD++a3Xu7HOd7kquZWamsrBgwedPr+kyoe/QM9xbdFa3wpMAtoBwd1pT4g2wlmqeEJCgi1VPjEx\nkdTUVJep5q5orSkuLiYpKYm4uDin53TsWMeMGQd4/fWfOOGESg4ciGXcuCzGjs1k376YZj2Pt1wN\nmZaXl5OZmem3JQIi/Pizx3UZsF9r/aW/GufiPtLjEhGluLi4yYLlmJgYMjIy3JZH8lb79u05fvy4\nx80xa2vh7bc78cILaRw7FoXZXM/ttx/ktttKiI31379J+woaO3fubNIua69KykG1TYEeKrRWgrcO\nF67VWr/gbWO9JYFLRBpXQ2bOPqi92TakpQ4ejObpp9P55z87AJCVVcXkyQWcddaxFl/bsYKGp+Dk\ny3yiP+ceResJdOA6G0BrvV4pFQ8M1Fp/5UuDvSGBS0Qad8HIcU4nkLs1b9yYyOOPd2X3bmOYccSI\nUh58sID09ObXHXBW+skfAcTX3pn05oKn1ee4lFJL7Q67AllKqXbAyYD8HxbCD9yVSnKUlJREZmYm\niYmJxMXFYTabSUxMxGw2+7VNMTExDBlSznvv/cSECYXEx9fz6aftGT26b0MV+uZdt6UB17rua+fO\nnezatcuWYu8shd4aDJ3x9XwRWC0t+RRtLeuklBqHUafwUoxdkIu01uP83F7pcYmI5G15KHfv97Yn\nFhcXR3V1tcsK9taaivaZfQUFMfzlL+l8+ml7APr0Oc7kyQc444wKbx7PxmQyER8f77ISv6cSWs6e\nUSlFbGysy7kyZ6S4b/AEeqiwF5Cutf6fUioJiHa2wWRLSeASkawlw2YWi4W9e/c2CUjWtVH213SW\nFGEvMTGR2traJuesW9eO2bO7snev0cO75JKjTJxYTKdO1V63E9zvfeYqgLgbUnXcC0yGCkOX1CoU\noo1rTsKBNx/IztaO2XMVuACqqhSvvZbCq692obraRLt2dfz5z0Vce+1h28aV1p2ka2pqqKtzvhtz\nYqJR+NcfgSsxMZGUlBTb9yoxMdF2rqvvmyRnBEfYBi6lVCrwFfAbrfUOh9ckcAlB83sFrjbHtP9Q\nLykpcTtUmJmZ6bFi/b59ZubNy2b1aqOkVP/+lUyZcoDBgytt6fzurmEymUhJSWk0JNncoULHTETp\nTYWuQA8VpgHttNY/KaWygPzmRBilVDTwDjAAGC2BSwjn/DUP48v8l9lsJj093WVJJntxcXGYTFGs\nWGFizpyuFBQY9Q6vvPIw995bRMeORmB0d1/rfJqn3pH9s5SUlFBbW4tSiqioqCbvkfmr0BboyhlX\nYmQV5gCHgeubeZ25wMsYOykLIVqZLxXoo6OjbUHAUzHgtLQ06uvr+PWvLXz44U7+8IeDREfX8/77\nnbjkkr68914HXHTqbLTWlJeX2zbt9NQrsm7wmZ6eTlRUFHV1dRQWFjYp4CvCmz8Dl1lrvQZI1Fpb\ngFJfL9CwCWWx1vpTwLf6NUJEmGBXlk9KSnKbZl9ZWWkbBkxI0Nx7bxHvv7+LoUOPUVoazaOPduOm\nm3qxdavzclNWdXV1TbY2cce+qry1Ioh9dflgf99Ey/lzqPC3wBRgJ/ARcJLWeqZPjVHqv4D1d7CT\nge0Yw4XFdufo6dOn296Tk5NDTk6OL7cRos3wNoHAUwV6b4YKnQ3bOcv6szKZTE7nybSGTz5pz1/+\nks7BgzGYTJrrrjvM2LFFJCW574J5Mx/lzYJtSbwIHbm5ueTm5tqOZ8yYEdA5rh4YvaTLgPbAc1rr\nMi/a7ep6nwF3yhyXEC3jTTKC/Qd5dXU1NQ4riF0lSjiu53J8j6sED4Bjx0y89FIqS5d2pq5O0blz\nDfffX8illx6jvt55piF4no/ypdKICD2BnuOaAxRqrZ8HXgEuauH1JDoJ4QfeVIGwzg1lZ2cTG9t0\n08jY2Fin17FWanccMlRKeezFtGtXz4MPFvL227s45ZRyDh2KYfLkHtxySya7djW/0oerSiPWIUFn\nuyqL8OLPHtcYrfUiu+NLtNYf+6GNjveRHpcQPvA1i85ZD83Vvzn76zgOv7kbRnRUXw/Ll3fgmWfS\nOXIkmuhozU03lfCnPx0kIeGXXpuvKf91dXVorYmOjrbNYzk+W2xsrO11V71QGU4MnECnw48Ebgbe\nwNiLa6TW+kkf2usVCVxC+KY565bsP7RdLTRuzpoqT0pLo3j++VTefbcTWivS0mp48MECRo2qJjq6\naWq7Y1s9BRh3w4j2zyNrvYIn4AuQlVJ9gVuBaOAVrfVuL9vqNQlcQviuJb0HZx/2JpOJHj16OA0i\njjUVm+OHH+KZOTODH3+MB+DCC+GFF6Bv31/uY+1R2S9gdhVgrOdXVla6nXdzt/uy2Wymb9++0hNr\nZWFbOcMdCVxCBJa3vQ9/b6lSVwfvvdeJ559Po6wsithYzUMPKcaOtXDwoOv7tGSrF3eBCyA1NdXr\nSh6ieQK6rYlS6kql1A1KqXZKqWFKqfNbcm0hRGiw3yolMTHR5Qe1LwuZvREVBddee5jly3dw6aVH\nqK5WzJwJp58eR25uO4/vtyZhOAtaJpOJuLjG68fs13O5Wtcl252EBtnWRAjhF629+/I33yQwa1YG\nO3caAef888uYNKmAjIzGqfupqanEx8e77WV5s57LWaFhZyn+kmLvX4FOzjgPqJVtTYSITIHYfbm2\nFpYu7cyLL6ZSURFFXFw9d9xxkFtuKSE21rivq6ry9rKysppVSd9x3ZoMFfpfoAPXm8CtWuuWzcp6\nvo8ELiFClLdJEC1VXBzN3LnprFzZAYCePauYMuUAZ55Z7jFwWZMsvOGpkr4kZ/hfoAPXX4FlwGda\n62Zu3O2ZBC4hQp8/hg2VUphMJpf7dQFs2JDI449n8PPPxoLl3/72KE8+WUuvXmavtjgRoSfQgetJ\n4BhwOhALfK21nuZDe70igUuI0GexWNizZ4/bc9q3b09ZWZnLoUWlFAkJCURHR9sqXGitm5xfXa1Y\nsqQzr7ySyvHjJhIS6njooQrGjoXS0qaLkCVohbZWD1xKqXYY67YqMArilmittyuj3kqm1tr9T24z\nSOASkSrchqhc7aJsvwbMYrGwd+9et8OK9r2knTt3ulwjduBADHPmdGXNmmQABg6s469/jeKccxqf\nF27fx0gTiMD1V4ztS7oD3TCqZVQ0s71ekcAlIlG4VHJw3Em5uLi4yTn2m1Fa3+MpqcM+C9BTT27t\n2nbMnp3B/v1GzcVbboGnnoLU1PD5PkayQASue7TWLzb8PR242L5eYWuQwCUiUTjs2usqC6+0tJTq\n6upGgckxYFgsFoqKimznOVt35Usv7fhxxZIlGbzySkeqq6FDB5g9G0aMyOP48dD+Pka6QFSHt40D\naK0LASm1LESEclU9vm/fviQkJDQ613HhblJSEn369GHAgAFkZmY2qe5eX19v2wgyKSnJaQV7e/Hx\n8Pjj0fzwA1x0ERw9CnffDVdckcEPP8T74WlFMLU0cD2slHpBKXWbUupk7LYiUUqltvDaQogGobxr\nr7VCRWVlpV+uZ63UYTI1/njSWrN3714sFovLYcW4uLhG1T369oWVK+G996B7d9i82cwNN/Tisccy\nKC2NCqnvo/BeS4cKpwJfAUOBIcApGJXh1wOpWuub/dtcGSoUkSsUkwrczU+1tNq6q+QO61Ykjkka\nMTEx9OvXz+X1jh2Dxx6DefM0tbWKTp3qmDWrmjvvjMfkz50JRYsEpciuUqoXRiC7Q2vt93qFEriE\nCB2uKsfHx8c73d/KOo8VExPTKEHDGXcZhDExMU12aXY2b2Yf6MEYztyxI4ZZs9JZty4agLPOgpde\ngsGDfXx40SqCWh1eKXWe1nqtr+/z4roSuIQIEa6SRqwbSULjihO+9Lo8LWJ2Frzssw/db4ap2LCh\nF1OmmCkuNhEVpbnzzhqeeCKW5GRfvwvCn/yVnKGUUiOUUnGeT/1FawQtIURocTb3lpiYSH5+PuXl\n5ZSXl9uSKnytrO54bUfuKmo4u1djmuHD9/HRR9u58cYStIaXXoqlX7963nwT5Hfj0OaxxwWglOoA\nnAskYiRg7NBaf9vKbXPVFulxCRFCHIfkSkpKnPbCoGn9QE+p6O5S381mc6M0e/senDclp+wrvW/d\nGsesWRl8/72R/XjBBcbGlf37u72EaAV+GSp0ceFfYSRiKKAG+EJrfaBZrfT93hK4hAhh7oYPHRM5\n4uLiiIqKcpts4ioIZWVlATgdknTchdlxqFAphdlsbpT8UV8P//pXGnPnduHQIYiJgfvvh6lToSHu\nigBotcDlcJNoYBjQA6M3dgj4XGvtn9zYpveTwCVECHM3l2XtndXW1rrsLXm6Hhh7bqWmptpet6/W\nYb/tCBjBMS0tDaBJsoazdlZXJ/Hww7BggfH+zEx49lm47DJwM3Ip/CQggcvJTTvxy7AiwFZvhxWV\nUiZgAdAPqAf+pLX+0eEcCVxChDhPqfu+VgJxdT1fykX52s4NG4xFy982fHpdfDHMnw+9e7u8lfCD\noASuhht3BXKA4Rip8au01pO8eN+lwCit9e1KqeHABK31ZQ7nSOASIsz5q4SVN3NZLSnpVFcHL79s\nDBeWloLZDA8/DA89BHE+pasJbwUscCmlugHnYwSrbsA+4L/AWq11vo/XMmmt65VStwA5WusxDq9L\n4BIizHmTGu/NgmtPgctTyr23i7qLimDiRHj9deO4d2+j93XxxZ6fVfgmkIGrP3A3MEdrvc8P11sM\nXAZcpbX+t8NrEriEaAPcBQ1v13y5K+xbU1NDbGwsaWlpXs2deVPNY+1aY/hwyxbj+IorjPmvHj2a\n/30QjQV0qFApFaP9uPNxQ63DjUB/+0QPpZSePn267bycnBxycnL8dVshRJC5SoG3X1zsrCKG/bFj\nQIqNjW2ykaS74Up3QbWmBp57Dh59FMrLISEBHnkEJkwAD7V/hRO5ubnk5ubajmfMmBGcOa7mUkr9\nHuiutX5SKZUMfAsM0FpX2Z0jPS4h2qji4mKne3iB85R6aw/LGoBcrSOz8rTWy9U9nPXE9u2D++6D\nd981jvv3N0pHye/RLROIbU38bRlwilLqv8BKYLx90BJCtF0Wi8Vl0LJWcXdWEaO4uLhRlQ53FTWs\n1TosFkuT89zdw1mFj+7d4Z13YNUq6NsXtm6F88+HG2+EggJfn174IqQCl9a6Qmt9rdZ6uNb6bK31\nx8FukxAiMFyVfzKZTF7vUmzdhNJdqaja2lry8/MbLT42m83N3gn5wgth82aYOdPINFy6FE44wRhO\nrK31+XLCCyEVuIQQwpF152PwXL8QIDo6mszMTBITE4lzyFlXSjkpuGu8x9U9vNmzy2w2UuZ//BEu\nuQTKyuDee+H00+GLL7x+VOGlkJrj8obMcQnRNnmqkGF/nqtKGc7mvACPtRStpadcvcfXntjy5TBu\nHOzZYxzfdhvMmQOyZ6VnQVuA3JokcAnRdlmDUl1dHVrrJpmA7t4DzgOZ4x5djnUMHXmTFu+NigqY\nPRueesrIROzUCZ54Am6/Hdm40g0JXEKIsOPL+ipvK9M726PLHWfVNpq7A/X27TB2LPy7YUXqkCFG\n9uFpp3n19ojjTeCKDlRjWlvPnj3ZY+2XCxGmsrKy+Pnnn4PdjKByldXnafFxRUUFsW4WUjle1xfO\n7uVtr6xfP1i92kibnzABNm6EM84wFjLPmgUdOjSrSRGtzXRY9+zZY8sokj/yJ1z/yC9f3nMW4KzJ\nF1beJFY4cvYeXzfBbHpNuOYa2LbNWPtlMsGLLxpBbckS2bjSV20mcAkh2obmZPVZRUVF2TIKExMT\nG/WKnF3XUVxcnF/mt1xJSoKnnzYqzp9zDhQXwy23wPDh8MMPrXLLNqnNzHE5S3EVItzIz7HBm/mk\n5tQadEz+sH6/PSWBNOdenmhtFO194AE4eBCioowU+unTjQAXqSIqOUP+wYu2QH6OfdOchInmBqHm\nJmd4cuSIsQbs5ZeNYJaRAfPmwdVXR+bGlRK4hAgz8nPc+vy1F5i/ffWVkbDx5ZfG8YgR8MIL8Ktf\nBbVZAReOtQqFECIiWats/PWv0LEjfPopnHii0RurqAh260KLBC4hRERpSfJHa4uKgjvvNNZ+3XYb\nVFfD44/DwIGwYkWwWxc6JHAFUHZ2NmvWrAFg0KBBrF27NsgtMkyePJnnn3/e5etjxozhkUce8es9\nhw4dytatW/16TYBdu3bxwQcf8Nhjj/HNN9/4/foifFgsFvLy8sjLy8Nisdi+npSU5DLzMFR06QIL\nF8L69XDSSfDzzzB6tPEnLy/YrQu+NrMAOdz8ECK5ryUlJbz++uvs2rXL79d+8cUXWbx4MZs3b+aG\nG27gtddes702ceJEpk2bxnvvvefXe65YsYKzzz6b3/zmN9x5550sXbq02df66KOP2LJlC1FRUWRk\nZHDTTTe5Pb+8vJw5c+aQmZlJaWkp999/PwCLFi1i//79xMbG8qtf/YrLLrus2W0S3vG0YDgpKSnk\ngpUzZ50FX39trPmaNs3odX36KUyZAhMnGsV9I5EErghSV1dnKyRqtXjxYkaOHIm5Ff4FdOvWjWnT\nprFq1SoqKysbvTZq1CjuvPNOiouLmxRRdeebb75hxowZlJaWcvPNN3P8+HE2bdrEDTfcwPDhw5kw\nYQIAW7dubdFke1lZGY899hhff/01AMOGDWPkyJF07tzZ5XvGjRvH9OnTyczMZNCgQVx11VVYLBYW\nLVpk612PGDGCiy++uFW+3+IX3lbfCAfR0TB+vLGA+YEHjG1Tpk0zFi6/8IKxrUqkkaHCILEfNszO\nzubpp59m8ODBdOzYkeuvv57q6mrbuQUFBVx11VWkpqbSu3dv5s+fb3ttzpw59OnTh+TkZAYNGsSH\nH37Y5D5PPfUUgwcPpl27dk22Q1+5ciXDhw9v9LVvv/2W0047jfbt23Pdddc12rfIF5dddhmjR4+m\nU6dOTV4zm82cdtpprFq1yqdrnnrqqbRr14777ruP2267jbvvvpuRI0cyfvz4Rud9+OGHTJkypVnt\nBli7di0DBw60HQ8ePJjPPvvM5fl5eXkcOHCAzMxMAFavXk1WVhaffPJJowCamprK+vXrm90uEbm6\ndoU33oD//MfY72vnTrjoIiOg7dsX7NYFlgSuEPHuu++yevVq8vLy2LRpE4sXLwaM3xRHjRrFKaec\nQkFBAf/5z3947rnn+PTTTwHo06cP69evp6ysjOnTp/P73/+eoqKiRtd+6623WLlyJUePHsXkUJZ6\n8+bN9OvXz3ZcU1PD5Zdfzi233MLhw4e5+uqref/99xu9Z9SoUXTs2JFOnTo1+e/o0aO9fub+/fuz\nadMmX75NAHzxxRf85je/sbX39ddf57777rO9vmLFCsaOHcv+/fsbvW/37t08/PDDTJ48mYcffrjR\n3ydPnszy5ctt5+7bt48OdkXkOnTowM6dO122ac2aNbRv355//OMfzJ8/n9WrVwPQrl07ampqbOcd\nP368Veb2Io2r+SsrbxMwPF0nFF1wAWzaBE8+CQkJRg3EE06AuXONKvSRIGKGCv25kK81ltmMHz+e\ntLQ0wAgM3333HQAbN26kpKTE1nvo2bMnt99+O2+99RYjRozgyiuvtF3j6quvZvbs2WzcuJFRo0Y1\nunZGRobT+x49erTR8MmGDRuora1l3LhxAFx55ZWcccYZjd6zwk/pTUlJSRQWFvr0nm3bttGhQwfW\nrVvH7t27+fLLL3nmmWdsPZ0PPviAJ554gvnz5zN8+PBGva5evXrxxBNPeHWfI0eONNqEMDY2lmPH\njrk8v6ioiC1btvDWW28BcO6553LOOedwxRVXsGjRIgCOHTvG9u3bm3w/hW+8KXhrTcBwt2C4JYVz\ngy02Fh56CK6/3qi28cEHxpzX4sVG5fnzzgt2C1tXxASuUGcNWgAJCQkUFBQAkJ+fz/79+23DbVpr\n6uvrOa/hJ3PJkiXMmzfPVlG8vLy8SfHP7t27u7xvx44dG/2meeDAAbp169bonKysrOY/mBsWi6VR\nr8Yba9asYfTo0VzYMLC/fPlyCgsLbYHr8ssv5/LLL29x25KSkjh8+LDtuLKykvT0dLfnn3jiibbj\nzMxMVq9ezd13382iRYtYsGAB6enpnHjiiT7N6YmmvJ2/8pSA0RbmwTIzYdkyWLkS/vxn2LLFqHt4\n003wl7+A3cdKmxIxgStcixH06NGDXr16sX379iav5efnc8cdd/DZZ58xbNgwAE455ZQmlRfcbXV+\n0kknsWPHDk5r2Byoa9euTYbY8vPz6dOnj+145MiRfP75506ve+655/LPf/7Tq2fbunWrx0w9R599\n9hm333677fjw4cPs3r2bIUOGeHzv7t27WbBgQZN2W2vWnXnmmbahzt69e/PVV1/Zzjl06BCnnnqq\ny2sPHDiQdevW2Y5NJhN1dXUADBgwgAEDBgDw2GOPMXPmTC+eVAjvXXyxUaR3zhxjs8rXXzd2YX78\ncfjTn4z1YW2JzHGFuCFDhpCUlMRTTz3F8ePHqaurY8uWLXz11VeUl5djMplISUmhvr6eRYsW+Zxm\nP3LkSHJzc23Hw4YNIzo6mvnz51NbW8uyZcvYuHFjo/f861//wmKxUFZW1uSPfdCqq6uztbm2tpaq\nqirbh3lVVRVff/01I0aMsJ0/ZswYbrvtNpdt1Vqzdu1azjzzTNvXNm/eTOfOnW09VHesQ4WzZ89u\n9Mf6Nfv5ueHDhzdaB/bNN9/w61//GjACoOMvB2effTb5+fm24927dzNy5Ej27NnD4MGDASNQZ2Vl\nNfolQPjOXwuIQ3khcnPExRkFerdsMQJZaamxgeWQIfB//xfs1vmXBK4AcrWlgrsekclk4uOPP+a7\n774jOzub1NRU/vjHP1JWVkb//v25//77OfPMM0lPT2fLli2cc845Lu/pzM0338zKlSttW5nHxMSw\nbNkyFi1aROfOnXn33XcbzaP5YtasWSQkJDBnzhzeeOMNEhISePzxxwFjiO/8889vNPy2d+/eJu23\n+v7775kyZQqVlZWNkkX+8Ic/sGHDBluyir8kJCTw4IMPMmvWLGbOnMnEiRNtQ3xXXXWVbQ7Symw2\n8+ijj/LII48wbdo07r77bnr37k1GRgaXX345L730EgsWLGDBggV+bWck8tcC4nBYiNwcvXvDP/9p\nDCH26AHffAPDhsEdd8ChQ8FunX+EVJFdpVQ08BrQE4gFHtdar3A4R4rs+tnUqVNJTU21JWQEwrBh\nw1i4cKFtCK2mpoaTTz6Z77//vslas0giP8fCn8rLYeZMYw+w2lro3NkYThwzxtjMMhSFXXV4pdSt\nwEla6/uUUh2B77TWWQ7nSOASbZb8HIvWsHUr3HMPWJciDhtmZB+efHJw2+VMOFaHfweY1vB3ExAh\nqxKEEKL19O9vLFx+4w1ITzeq0J92mlGRo7Q02K3zXUj1uKyUUknAR8ArWuu3HV7T06dPtx3n5OSQ\nk5Mjv6mKNkF+jkVrKy01kjjmz4f6eiOQzZ0LN9wQnI0rc3NzGyWIzZgxI7yGCgGUUj2AZcALWuu/\nO3ldhgpFmyU/xyJQvvvO2Ljyiy+M45wco5hvw7Rz0ITdUKFSKg1YBTzoLGgJIYTwj5NPhnXrjO1T\nUlIgNxcGDzYqcrgpEhMSQqrHpZR6FrgG2AYoQAMXa62r7M6RHpdos+TnWATD4cMweTL87W9GsYbu\n3eHZZ+GKKwI/fBh2WYXekMAl2jL5ORbBtHEj3HWXsfYLjOrzL7wAgVwzH3ZDhUIIIYJnyBAjeL34\nIrRvD6tWGaWkQo30uIQIIfJzLEJFcbGRPn/vvYEdLpQeVxtz11132Uom+fPcQFm3bh39+/cPdjOE\nEF5ITYUJE4KTIu+J9LgCJDs7m4ULF3LBBRcEuylh4b///S+///3v2bt3b7CbElCh/nMsRGvzpscV\nMduauFNWVkZBQQF1dXUkJSXRrVu3JjsFt7a6urqIrtHnyLrViBBCOGrzQ4VaawoKCti2bRs7duxo\nsj13ZWUle/fupaamhvr6esrKyti3b1+T61RVVVFaWkpFRYXPbbj55pvJz89n1KhRJCcnM3fuXPbs\n2YPJZOK1114jKyvLtmXGNddcQ9euXenYsSM5OTn8+OOPtuuMGTOGRx55BDB6JD169OCZZ54hLS2N\nbt26sXjx4made/jwYUaNGkX79u0ZOnQo06ZN49xzz3X6LNZ2L1iwgG7dutGtWzeefvpp2+vV1dXc\ne+JOhn4AABBESURBVO+9dOvWje7duzNhwgTb1vXWdlhlZ2fz9NNPM3jwYDp27Mh1111HdXU1FRUV\njBw5kgMHDpCUlERycjKFhYV8+eWXnHHGGbRv356uXbvywAMP+Pz/QggR/tp84CooKODw4cPU1tZS\nXV1Nfn5+o+Bz7NixJrugOga3o0ePsmvXLvbv309eXl6TjRY9WbJkCZmZmXz88ceUlZU1+sBdu3Yt\n27ZtY9WqVYCxP9ZPP/1EcXExp556KjfeeKPL6xYWFmKxWDhw4ACvvvoq99xzD6UuCo+5O/fuu+8m\nKSmJ4uJiFi9ezN///nePvZ3c3Fx++uknVq1axZw5c1izZg1gbGWyceNGvv/+ezZt2sTGjRuZNWuW\n7X2O13333XdZvXo1eXl5fP/99yxevJiEhARWrlxJRkaGbd+v9PR0xo8fz7333ktpaSk//fQT11xz\njds2CiHapjYfuEpLS5sEprKyMtuxyWRq8mFqP0yotWb//v1oramvr0drzdGjR5vV83K2M/GMGTOI\nj4/HbDYDcOutt5KQkEBMTAyPPPIImzZtahJIrWJjY5k2bRpRUVFcfPHFtGvXzulOye7Ora+vZ9my\nZTz22GOYzWb69+/PLbfc4vFZHn30UeLi4hg0aBBjxozhzTffBGDp0qVMnz6dzp0707lzZ6ZPn87r\nr7/u8jrjx48nLS2NDh06MGrUqCb7XDk+w65duzh06BAJCQle7XoshGh72nzgcjZXZf+1Dh06EB0d\nbQteSim6du1qe926Y689pZRt+Kulunfvbvt7fX09kyZNok+fPnTo0IHs7GyUUpSUlDh9b+fOnRs9\nS0JCAsdc1Gpxde7Bgwepq6tr1A774TxnlFKNzs/KyuLAgQMAHDhwgMzMTKevOZOWluZV+wEWLlzI\n9u3bOeGEExg6dGij3ZaFEJGjzQeutLS0Rj2qqKgoOnXq1Oi4T58+pKWl0aVLF7Kzs+nQoUOj1x2T\nJrTWxMXF+dQOV0Nv9l9funQpK1asYM2aNRw9epSff/4ZrXWrZpl16dKF6OjoRvN6njL5tNaNzsnP\nzycjIwOAjIwM9uzZY3ttz549ttd84ez71bt3b5YuXcrBgwd58MEHueqqq6isrPT52kKI8NbmA1eH\nDh3o2bMnnTt3pkuXLvTt25fo6MbJlFFRUaSkpJCWlkZCQkKj15RS9OzZ09YrU0rRrVs329Cet9LT\n09m9e3ejrzkGJIvFgtlspmPHjpSXl/Pwww+3emadyWTiiiuu4NFHH6WyspJt27axZMkSj++bOXMm\nlZWVbNmyhUWLFnHdddcBcP311zNr1ixKSkooKSlh5syZ3HTTTT63Ky0tjUOHDjUa1n3jjTdsvc/2\n7dujlAp49qcQIvgi4l99YmIiXbt2JS0trUnQ8kZcXBz9+vWjX79+DBgwoFGPzFuTJk1i5syZdOrU\niWeeeQZo2qu4+eabyczMpFu3bgwaNIizzjrLp3v4EuTsz50/fz5Hjx6la9eu3HLLLdxwww0eA/Pw\n4cPp06cPI0aM4MEHH7RlRU6dOpXTTz+dk046icGDB3P66aczZcoUn9vbr18/rr/+enr16kWnTp0o\nLCzkk08+YeDAgSQnJzNhwgTefvttn3+BEEKEP1mALJqYNGkSRUVFLFq0qMlre/bsoVevXtTU1Ehv\npxXIz7GIdFLySXhl+/btbN68GYCNGzeycOFCrrjiCpfnywerECKYpHKGwGKxcP3111NQUEBaWhoT\nJ05k1KhRLs+XihZCiGCSoUIhQoj8HItIJ0OFQggh2hwJXEIIIcKKBC4hhBBhpc0kZ2RlZUnSgAh7\nWVlZwW6CECGvzSRnCCGECH9hm5yhlBqqlPos2O0INbm5ucFuQtDIs0eeSH1uiOxn90bIBS6l1ERg\nASC1fBxE8g+zPHvkidTnhsh+dm+EXOACdgGXB7sRQgghQlPIBS6t9QdAbbDbIYQQIjSFZHKGUioL\neFNr3aQ8ulIq9BoshBDCbzwlZ4RyOrzThnt6ICGEEG1byA0V2pGelRBCiCZCcqhQCCGEcCWUe1xC\nCCFEE2EbuJRSlyul3gh2OwJBGV5WSv1PKbVGKdUr2G0KpEhckK6UilZKLVFKrVVKbVBKud4grY1R\nSpmUUguVUusann9AsNsUSEqpVKVUvlLqV8FuSyAppb5u+Hxbo5Ra6O7cUE7OcEkp9SxwIfBdsNsS\nIJcBZq31WUqpocAzDV9r8xoWpN8EHAt2WwLs90CJ1vpmpVRHjJ/1FUFuU6CMArTW+hyl1HBgNpHz\n8x4N/BWoCHZbAkkpZQbQWl/gzfnh2uNaD9wV7EYE0DnAJwBa6/8DTg9ucwIqUhekvwNMa/i7CagJ\nYlsCSmv9EXBHw2FP4EjwWhNwc4GXgQPBbkiADQYSlVKrlFL/bvgF3aWQDlxKqduUUpuVUt/b/fc0\nrfW7wW5bgCUDpXbHtUqpkP5/5y+RuiBda12htS5XSiUB7wJTgt2mQNJa1yulFgPPAZEyJXArUKy1\n/hQXy4HasArgL1rrizA6JW+4+4wL6aFCrfVrwGvBbkcIKAOS7I5NWuv6YDVGBIZSqgewDHhBa/12\nsNsTaFrrW5VSqcBGpVR/rXVlsNvUysYA9UqpEcDJwBKl1GitdXGQ2xUIOzBGV9Ba71RKHQK6Avud\nnRwRv7W3AeuBkQBKqTOBzcFtTlBE1G+gSqk0YBXwoNb678FuTyAppX6vlJrUcHgcqAPa/C9qWuvh\nWuvztdbnY8xp3hwhQQvgNuBpAKVUBsYv6gWuTg7pHpew+QAYoZRa33A8JpiNCZJIW3D4MNABmKaU\negTj+S/WWlcFt1kBsQxYpJT6L8Zn1PgIeW57kfbzvhDj//nnGL+k3OZuVEkWIAshhAgrMlQohBAi\nrEjgEkIIEVYkcAkhhAgrEriEEEKEFQlcQgghwooELiGEEGFFApewUUrdopR6opnvnaSUOlUp1U0p\ntV4p9V+lVNeG125USl3j4n15/9/e+QdpWVVx/POdBaRVU4LGxVZ3CJv8wUKYyWSjW/JTJacpQ4pS\nAnVTG8oBIikHG8wfaJMjCiNQa0oqohX9wnBwjV1B18xhWiBBJX8k9kNHB6gGtdMf5zztw7vP7rvM\nLq473c/MM3v3Pue5597zvu+99zzv854jaUB3+t0dJH1GUlUn5wdJ+sJB0HtkRMP+bUn96ZJGRLnD\nH2D2BuX6I+liSRWSRkn6Tjd17ZP0oKQaSZsKzg+RdH/IPCppmaSB8ePlRkmbJL2RizaevReHStor\n6XO5tm6Ka7ZJej7kV0laKGmXpAmSRsTv6RLvAtLClSjlgH/YJ6kaqDWzPwBTgBvwCPZTJA0EPm1m\n9/WUvh7m63gsyI4YBZx7EPSOBJ6L2Gx5ZgBHR7m3bVNKuf7MByrMbLOZXdNNXf8ws0md6J0LrDOz\nSWb2CTx7QL2ZrYzIE1OBLWZ2ZhzZovsVPP7h5VlDZjYnrrke+EnIn29mVwFrQ6YVGC5pWDfHlegB\n0sKVKETSbEktsZu9LuoGR/TmRkm3S9oR4pcC90d5N1AZx17gCnyiKKevRtL68NQaJY2UNEvS7Di/\nNNLZIGm+pKmxC8521KslHS6pTp6/6neSpuXaP0TSmmj7cUnjJJ1NW0y4fpKujfH9Xm35gOYDn5J0\nkaQGSROivYmSGqLcEPpa8jo7sqWk/mGT0yUtyMmdDEwCFsnjFA6UtFJSk6SfhTfz3hjr+jhGlOiq\nk7QuPJGnJF0W9aOjnUZJayVVh81bJP08xrwwN578OLN4oYq6M0L3w3H9cZJmAFXAvdGHe0J2Wshs\nkOfY6if37FdJ+qWkLZIuKPf+KOCvwHmSxsbmaC5wSxeu+xIeWmiAupbnKx9qbDXwtQPuaaLnMbN0\npAMzA7gQz300AtiEB/MFX5TOwb2or0bdONxjAI+lODzKhwLLgCXAMGAFnpZlKTCzQOdzwAB8Upgc\ndaOAJ4Bq4KGoexjYFOUNwGHRx+OjbgZwDVAHPFWg50SgOa4bDkzKtfshPDbanKgTsBUP8lkH3B31\nDcCEKE/EA0AfBuwABscxtURvqS0fwONOnpG1WyLfAIyP8j7gmFw/T8G9gvqoOw5oKrm+DmjFQyUN\nxIOXvj/sWRsy54a9a/AF4Ah8E/soMLponFF+Of5eClRF+Urgytxr2T+zGfC+sE1lnP8+7ulcCKzN\njWFbgR0yXTXAxoLzAqbj6X5eA9YA1bnz7a4DxgKrojwTWFL0/i94PTJbHAs82duf03RYilWYKOR4\n4DFrixXWDJwU9XdEXVNOfgg+AWJme4lcSpJuAb4H3IYvfA9IutvaR/kWcELWppltllRtZi9JqpT0\nMWAbcIykU4DXzWyPpBOAJZLAJ8zMA3y6dEBmtlXSMuBefFLPdueK41/AUfKs2nvxBbh/JzZStLtH\n0hXAcnzxW1kiV2rLJtyWLeXaBl41sxej/AruxdbiHuD5ITeo4PqNZvYWnv6mFV+oh5pZFpx5A3Ad\nfgtus5m9ASCpBfhwB33J8xdgsaTd+OaiOSebl/8g0GpmWVLEJmB8jD1LAvsicEihFTrnTOBOM7sj\nPNh5wM3AeZ1cczEwTNJvQudISfPMbHcXde7CF+NEL5NuFSaK+BMwRp5CXbh38DS+kz8tZD6ek/8b\nHhD2f8QtrH+a2U585w9QQftJSvgEujX0IOkj+EQN8GtgER4p/SFgMR6ENevnBeZZU+cBv4r6dsE5\noz+Hm9lkfKe+OCdbAZyFezfT8NuDldG3/9D2Ofk37oUBnBztVgEfNbPPApOBG7V/HqEiW24v7V+O\nvL79hhB/twE/iDFPof1CCTBaTiW+SG4HXpZUG+c/GXUCTpQ/1FABjAG2FI2zpA/LgelmNgNPeJjV\nv43bMmNntP+e+L8uN/b891blIv8XnZ8FTAMwszdz/S68TtIQYIyZnWpmZ5vZWPx9NL2M7jyD8Pd6\nopdJHleiHWbWKmk1sBH/8Deb2RpJzcBdkj6P7z6zrLyN+KT3Uq6Zb9H2Bfid+O2yJ8zs9VJ18Xcu\nsFzSHPx9OTPqfwoswNO5H43fbvpFnLss+tMPn/BnAh/oYFg7gAXypxtFW3bhjcCP8dtnV0l6JOqf\nDX3PArWSZuETdkN8j7U9bPWKpCp55P63gEU57yqz5X0FtqzroJ+PA9dL+jP7T+5Z+Vrgh5LqcQ/v\n6oI2+uMPFQwGFprZa5IuAW6NxfNN2uy7D79teBSw2sz+KGkF8KP8OEv6cBfQLGkP7mlnD5M04xuN\n78bYX5V0NfCIpLfxfEvzgNKnNMs99HFSeIPZJmc2UA8slfQN3Fv+O+2zoufb/TJ+mzbPCvy1X0zX\nGAOs76Js4iCSosMnuoyks/AMrU9KGot/tzFO0rHATWZW+Mh74p0jFsR6M/tiF2RrgHvM7LRysu80\nknaZ2dDykge9Hw24jdZJWgl828ye7+1+/b+TbhUmDoSd+HcbG/Bd9TcBzOwFYHM8FZdI9ASDJD3Y\nmx2IpywnRrkWeCYtWu8OkseVSCQSiT5F8rgSiUQi0adIC1cikUgk+hRp4UokEolEnyItXIlEIpHo\nU6SFK5FIJBJ9iv8CxZpHwIQGo8YAAAAASUVORK5CYII=\n", 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TJ+/h/fcbOPlkKCuDyy+Hs88G5wRBK+vEuf8WtD92FaqYkze3pSD0dNqruKYppZ5WSl2v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\nEjY+/tg4HjUKnnwSjj46qMuEPRLjEgS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R0QwZMoRrrrmG559/HoClS5cybdo0UlJSSElJ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\nCoIgCKqKUFxBEARBVRGKKwiCIKgqQnEFQRAEVcX/AOcuWac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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1575,16 +1553,16 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 38, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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vPtjCxPEvGiG+ZWWeQuXGHSfwJeASgFKqOZCjtf7Z0xMT3COofn2ip00j56GH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\nRU5ErkJggg==\n", 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eNgE6o4i+112HlcuXc3lohmECwpcTOArA3QAeBWACsAHAeiI6E9JJhYET2DEGX338KO69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\nX9hfLwXwgIfzQvV8GB905Cggb+n0rt/L3+9ZUlJ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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1626,7 +1604,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 39, "metadata": { "collapsed": true }, @@ -1641,7 +1619,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 40, "metadata": { "collapsed": false }, @@ -1676,16 +1654,16 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 41, "metadata": { "collapsed": false }, "outputs": [ { "data": { - "image/png": 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5zaLfAFD6dandg/rHzf/olgPtoXjtp/UQsLK7fdXicwC/BN4B3MBnwHbg3K5v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\n9cxTDBsxrNNaqnx1805tmMrqcasBqI5WM2zokee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EGkMkZSfx6YZPGXvRWEKhEFVlVZx/9vmkp6ezdu1aAEaOHInNZvwpbdq0ifLy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\n1laeefYZVn5qZZfM9s3NzZx80snH3/kgUoASKUP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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1746,21 +1724,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.5.2" } }, "nbformat": 4, diff --git a/code/ch11/ch11.ipynb b/code/ch11/ch11.ipynb index 9012c306..39b62c9c 100644 --- a/code/ch11/ch11.ipynb +++ b/code/ch11/ch11.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Copyright (c) 2015, 2016 [Sebastian Raschka](sebastianraschka.com)\n", + "Copyright (c) 2015-2017 [Sebastian Raschka](sebastianraschka.com)\n", "\n", "https://github.com/rasbt/python-machine-learning-book\n", "\n", @@ -35,31 +35,29 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-06-24 \n", + "last updated: 2017-01-03 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.2.0\n", + "CPython 3.5.2\n", + "IPython 5.1.0\n", "\n", - "numpy 1.11.0\n", - "pandas 0.18.1\n", - "matplotlib 1.5.1\n", - "scipy 0.17.1\n", - "scikit-learn 0.17.1\n" + "numpy 1.11.3\n", + "pandas 0.19.1\n", + "matplotlib 1.5.3\n", + "scipy 0.18.1\n", + "sklearn 0.18.1\n" ] } ], "source": [ "%load_ext watermark\n", - "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scipy,scikit-learn" + "%watermark -a 'Sebastian Raschka' -u -d -v -p numpy,pandas,matplotlib,scipy,sklearn" ] }, { @@ -119,17 +117,7 @@ }, "outputs": [], "source": [ - "from IPython.display import Image" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ + "from IPython.display import Image\n", "%matplotlib inline" ] }, @@ -142,13 +130,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from sklearn.datasets import make_blobs\n", + "\n", "X, y = make_blobs(n_samples=150, \n", " n_features=2, \n", " centers=3, \n", @@ -159,16 +148,14 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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NZqOqqqqw9PD777+f1qxZo5nRGO3c0aaRpiPd1azMQpVTeYnU1qeyNiK19cHE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\nMAzDWBI2UAzDMIwl+f+GwMU+ixt83wAAAABJRU5ErkJggg==\n", 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c5DBxchmjO5UXa1MvhDf2rTJLqZhRaV6KmVUzvpViZnVNpcrJvxu89D6zEuMm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\n/uVf/qXsknwrZmnUxOfZZ5/Fnj17dCVAMudONUK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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -187,16 +174,14 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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ZSc8xXWEymXh77BjWzH4vJ4A5+z3eHjvGq+utvh7HcBcj6zOyNjC2Pmfaypcv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\nCS+e9z2+qkUPlIEyGF27duWNt8bw885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bcxoj7jkKcYdh6vRZDBw4sECa1D6pgqN1H5Qy\nUAqFwitoNT5aSgrlxzh4ouGgKiDrHspAeREj18wCY+szsjbwPX161LMzG4fX2ibzaoebzzsyDn37\n9uXCgcV2u/U+OhnKNOzLp59+mq85zJ8/n40LhrFmSN6kDmd1CPODr312eqIqSSgUCp/DWR0+rZjT\n0e+pbvu8dUag9TWOH/uDRx0UP3+gFmw+diTfc1D7pLyDMlA6YNRfOWaMrM/I2sC/9TmKMZmNQ+59\nUGDfONSsVYc9B/J21gXYewxqNqyd77l5Y5+UP392eqGy+BQKhc/hrOSRlnR0ayZOnEjcYexmB8Yd\nhkmTJuV7fmqflJeQUnrlkXMpY7J9+/bCnoJHMbI+I2uT0j/1XblyRZaOipBbRiDlspuPLSOQpaMi\nZFJSkiwdFSGn9LL/enJycp4xZ82aJUOKIR9pgHy7e86/IcWQs2bNKvA8d+3aJUtHRcguTcLk292R\nXZqEydJREXLXrl3uyLfgj5+dVm7YA5d2Qy3xKRQKXXG3h5KrkkcbN25kzZcb6fBoG/b+n0lTh9uB\nAwfStWtXRowYweZjR6jZsDYnN0/Kd/aeNQUp/aTIHyqLT6FQ6IYee4Nc9p6qNYLxEybq2uE2KSmJ\nkSNHcvzYH9SsVYeJEydSvnz5Ao2lcI3K4lMoFF5Frx5KWhMQ9MgIBNtNvI9Gw54DP1Cz2mK3NvEq\n9EElSeiA0WtmGVmfkbWBd/Xp1UNJawKCHtqSkpJ49b+D+PJl2PgajO6c8++XL8Or/x3EuXPn3L5G\nQTH6d1MLuhgoIUQ7IcQfQoijQojheoypUCj8C732BnmzUOvIkSNpcbv9KustbocRI0bodi1F/nHb\nQAkhTMCHQFugHtBLCFHH3XH9CaPvVzCyPiNrA+/qy2/6tzO0FGrVQ9vxY3/woJNNvMcLsIlXL4z+\n3dSCHjGoxsAxKWUCgBBiOfAY8IcOYysUCj8hJiaGUcNfZuvBvDXvdh81sTife4P0ijE5wxObeBX6\noccSXwUg0er49I3nigxGXys2sj4jawPv6vN2DyU9tHliE69eGP27qQWvZvH169ePqlWrAhAZGUnD\nhg0tbqz5w1DH6tibx2Z8ZT5G0HcyIYmxY8fyR9IZ2j/bksUxMfz000/EWRU/1eN68fHxuow3dfos\nOgwdRMMq0PGuHM/p29/hxUFDLfukCuPz00ufLxzPmDGD+Ph4y/1fK27vgxJCNAHGSCnb3TgeQc4u\n4Xdznaf2QSkUCp/k3LlzjBgxguPHjlCzVm0mTXJvE6/COV5rtyGECACOAC2Bs8APQC8p5eFc5ykD\npVAoFArNBsrtGJSUMgsYDGwBfgeW5zZORif3corRMLI+I2sDY+szsjYwvj4t6BKDklJuBlS6i0Kh\n0Iy7NfsUxkfV4lMoFF5Hj5p9Cv9FtXxXKBQ+ibllu23NPsct2xXGw2sxKIXx14qNrM/I2sA39elV\ns88XtemJ0fVpQRkohULhVfSq2acwPspA6YB5M5pRMbI+I2sD39SnV80+X9SmJ0bXpwUVg1IoFF5F\nxaAUKgblRYy+VmxkfUbWBr6pT6+afb6oTU+Mrk8LqqOuQqHwOuZ2GuaW7e3b1WSxGy3bFcZELfEp\nFAqFwquoJT6FQqFQ+DXKQOmA0deKjazPyNrA2PqMrA2Mr08LykApFAqFwidRMSiFQqFQeBUVg1Io\nFAqFX6MMlA4Yfa3YyPqMrA2Mrc/I2sD4+rSgDJRCoVAofBIVg1IoFAqFV1ExKIVCoVD4NcpA6YDR\n14qNrM/I2sDY+oysDYyvTwvKQCkUCoXCJ1ExKIVCoVB4FRWDUigUCoVfowyUDhh9rdjI+oysDYyt\nz8jawPj6tKAMlEKhUCh8EhWDUigUCoVXUTEohUKhUPg1bhkoIUR3IcRvQogsIcTdek3K3zD6WrGR\n9RlZGxhbn5G1gfH1acFdD+og0AXYocNc/Jb4+PjCnoJHMbI+I2sDY+szsjYwvj4tBLrzZinlEQAh\nhMu1RCNz+fLlwp6CRzGyPiNrA2PrM7I2ML4+LagYlEKhUCh8EpcelBBiK1DW+ilAAqOllOs9NTF/\n4s8//yzsKXgUI+szsjYwtj4jawPj69OCLmnmQojtwCtSyp+dnKNyzBUKhUIBoCnN3K0YVC6cXkzL\nZBQKhUKhMONumnlnIUQi0AT4SgixSZ9pKRQKhaKo47VKEgqFQqFQ5AevZvEJIcYJIQ4IIX4RQmwW\nQpTz5vU9iRBishDisBAiXgixWghRorDnpCdG3JQthGgnhPhDCHFUCDG8sOejJ0KIBUKI80KIXwt7\nLnojhKgohNgmhPhdCHFQCPFSYc9JL8T/t3f3IFZcYRjH/49IRGKwsRGXVURCcAu1MYiV4uLG4GqZ\nDwjRVkUIpIiKSWEhNiIGK1GIuFikUXBBN8RGQhbBSMQvtvILTBUIEhA/Hos5wkXUu8q5c+aO7w+W\nnVkOzHP2cuedOefMvdIsSZPpHHlV0o+lM/WCpBmSLks686Z2dS8zP2B7me0VwFmgTf/888CQ7eXA\nFPBD4Ty5teqhbEkzgJ+B9cAQ8KWkT8qmyuo4Vd/a6Anwne0hYBWwrS2vne1HwJp0jlwOfCZpZeFY\nvbATuN6tUa0FyvbDjt0PgWd1Hr+XbP9m+0V//gQGSubJzfYt21N0WQzTR1YCU7Zv234MnAI2Fc6U\nje2LwL+lc/SC7Qe2r6Tth8ANYEHZVPnY/j9tzqJayNaqeRhJA8AG4Gi3trU/qCtpn6Q7wFfA3rqP\nX5OtQCwYabYFwN2O/Xu06CT3vpC0iOpOY7JsknzS8NdfwANgwval0pkyOwh8zzQKb/YCJWlC0t8d\nP1fT740AtvfYHgROAjtyH7+XuvUttdkNPLY9VjDqO5lO/0JoCklzgF+BnS+NzvQ128/SEN8A8Kmk\npaUz5SLpc+CfdAcsuozI5HwOCgDbw9NsOgaMAz/lztAr3fom6VuqW9e1tQTK7C1euza4Dwx27A+k\nv4U+IGkmVXE6Yft06Ty9YPu/9CEII0xjvqZPrAZGJW0AZgMfSfrF9jevalz3Kr4lHbubqcaOW0HS\nCNVt62ia6GyzNsxDXQKWSFoo6QPgC+CNK4r6UNcr1D52DLhu+1DpIDlJmidpbtqeDQwDN8umysf2\nLtuDthdTved+f11xgvrnoPanIaMrwDqqlRxtcRiYA0yk5ZNHSgfKqW0PZdt+CmynWn15DThlu00X\nTGPAH8DHku5I2lI6Uy6SVgNfA2vTcuzL6QKxDeYDF9I5chI4Z3u8cKZi4kHdEEIIjRRftxFCCKGR\nokCFEEJopChQIYQQGikKVAghhEaKAhVCCKGRokCFEEJopChQIYQQGikKVAghhEZ6Dm7jrGQMHIZ5\nAAAAAElFTkSuQmCC\n", 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v0rdvX6pVq4abmxu1a9dm8ODBZGUZ9jnUqlWLPn365Gl/44038Pf312mbO3cuDRs2pGTJ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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -289,10 +274,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -308,16 +291,14 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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XXoFnn826EjMzs/KUeXDKlz4H7zhgMPCEpDHAKODjx9hGxPvA08D49NCuJFOO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\nB3jkkRxPPnm7w5OZWUYcnKx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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -358,16 +339,14 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 8, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -424,16 +403,14 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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Ccf1g5ihQiSmcceZZIbmufHexi+n6/KHe+aACTe8Siii2umQR8NTv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\npR5VSu1QSuUrpd5QSp0S6T5ZiYmLspVSA5RSO5V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z56lQoQJdu3Z1KPaoMDVr1mT/ge949913Wfb+e6zcY3TM6tapxbR/jGHcuHFU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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -473,16 +450,14 @@ }, { "cell_type": "code", - "execution_count": 11, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -535,10 +510,8 @@ }, { "cell_type": "code", - "execution_count": 12, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "data": { @@ -547,7 +520,7 @@ "" ] }, - "execution_count": 12, + "execution_count": 11, "metadata": { "image/png": { "width": 400 @@ -562,10 +535,8 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "data": { @@ -624,7 +595,7 @@ "ID_4 4.385722 0.596779 3.980443" ] }, - "execution_count": 13, + "execution_count": 12, "metadata": {}, "output_type": "execute_result" } @@ -659,10 +630,8 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": { - "collapsed": false - }, + "execution_count": 13, + "metadata": {}, "outputs": [ { "data": { @@ -733,7 +702,7 @@ "ID_4 3.835396 6.698233 8.316594 4.382864 0.000000" ] }, - "execution_count": 14, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" } @@ -756,10 +725,8 @@ }, { "cell_type": "code", - "execution_count": 15, - "metadata": { - "collapsed": false - }, + "execution_count": 14, + "metadata": {}, "outputs": [ { "data": { @@ -816,7 +783,7 @@ "cluster 4 6.0 7.0 12.444824 5.0" ] }, - "execution_count": 15, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -836,9 +803,8 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 15, "metadata": { - "collapsed": false, "scrolled": true }, "outputs": [ @@ -897,7 +863,7 @@ "cluster 4 6.0 7.0 8.316594 5.0" ] }, - "execution_count": 16, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -915,10 +881,8 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { @@ -975,7 +939,7 @@ "cluster 4 6.0 7.0 8.316594 5.0" ] }, - "execution_count": 17, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -983,6 +947,7 @@ "source": [ "# 3. correct approach: Input sample matrix\n", "\n", + "row_clusters = linkage(df.values, method='complete', metric='euclidean')\n", "pd.DataFrame(row_clusters,\n", " columns=['row label 1', 'row label 2',\n", " 'distance', 'no. of items in clust.'],\n", @@ -992,16 +957,14 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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S5JuBf8rMBwM3As8E/gT4Mj2sLxYRtwfWA0cCv2h6HkmSpNWiSRCbBD5cb98M7JKZvwJe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\nBT4F7AY8aencMQ1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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1043,16 +1006,14 @@ }, { "cell_type": "code", - "execution_count": 20, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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sTLGxsZoyZYqKi4vl9/sDXrOhoUEPPfSQ+vXrp8jISN1xxx365JNPrPoVAMARmmaEgr2R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\nxjouQuYrsAAAAABJRU5ErkJggg==\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1068,7 +1029,7 @@ "row_dendr = dendrogram(row_clusters, orientation='left')\n", "\n", "# reorder data with respect to clustering\n", - "df_rowclust = df.ix[row_dendr['leaves'][::-1]]\n", + "df_rowclust = df.iloc[row_dendr['leaves'][::-1]]\n", "\n", "axd.set_xticks([])\n", "axd.set_yticks([])\n", @@ -1104,10 +1065,8 @@ }, { "cell_type": "code", - "execution_count": 16, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1144,10 +1103,8 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 20, + "metadata": {}, "outputs": [ { "data": { @@ -1156,7 +1113,7 @@ "" ] }, - "execution_count": 5, + "execution_count": 20, "metadata": { "image/png": { "width": 500 @@ -1171,16 +1128,14 @@ }, { "cell_type": "code", - "execution_count": 17, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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WNnpe+BSPnlTJkPiqpDRMKUvnT78FXVApaFLQFEjhFUcy++FZ+hLu6OjKBkfe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\nmxgeTvq+V6/94fee9u3bRzqdym7r1dn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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1206,16 +1161,14 @@ }, { "cell_type": "code", - "execution_count": 18, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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v4LMxQ5k+8nXWzv2KiGe1woAGg4GNiRuoXi2QVV9NZ+u6b6jZ4HFO/LKfUqV9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\nt82hJeyMqVxi29a0hJ2xJFdsTdDOTcTtjFW5Tda3YdZxpH6AW3Du4Z0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tBtdyMiWZ9UvfZfXsafTp04frr7/evk/79u3Ztm0b06ZN48NVKzh79iz169Vn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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1258,16 +1211,14 @@ }, { "cell_type": "code", - "execution_count": 19, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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zGDpsGIMUaQr7oHzE3rIHzi6JYDAY8Pzzz+PNufNwS7fu6HZ/X3RM6I3qqspa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\nQohIAKsALJVSfqCwiWaPvaOyu3rstdL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7tuPpbbu30969e22+xk6dOnHTTTexZv4sdq5PNo63uLCQneuTWb8okQERo/AP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\nGQyaJEmSMhg0SZIkZfj/hsMYhadW6SQAAAAASUVORK5CYII=\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1315,6 +1266,7 @@ } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "language": "python", @@ -1330,9 +1282,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.0" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch12/ch12.ipynb b/code/ch12/ch12.ipynb index 6930f3f6..979ba574 100644 --- a/code/ch12/ch12.ipynb +++ b/code/ch12/ch12.ipynb @@ -35,23 +35,21 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Sebastian Raschka \n", - "last updated: 2016-05-28 \n", + "last updated: 2017-07-29 \n", "\n", - "CPython 3.5.1\n", - "IPython 4.2.0\n", + "CPython 3.6.1\n", + "IPython 6.0.0\n", "\n", - "numpy 1.11.0\n", - "scipy 0.17.0\n", - "matplotlib 1.5.1\n" + "numpy 1.13.1\n", + "scipy 0.19.1\n", + "matplotlib 2.0.2\n" ] } ], @@ -116,17 +114,7 @@ }, "outputs": [], "source": [ - "from IPython.display import Image" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": true - }, - "outputs": [], - "source": [ + "from IPython.display import Image\n", "%matplotlib inline" ] }, @@ -153,10 +141,8 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, + "execution_count": 3, + "metadata": {}, "outputs": [ { "data": { @@ -165,7 +151,7 @@ "" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": { "image/png": { "width": 600 @@ -195,19 +181,17 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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EnDOYTz75RGbMmCEzZ86UhQsXyocffijbbLON/OhHP5Ltt99eyAfj+frrr2XdunVy4IEH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f2pVWJtHuXxRtEF5XdgRvlJ7DO/UfAn8tk3WKoMzkhxhzOxbPv5KS3Yl9b2Ri4oxr8OaePJlO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\nRK5CYII=\n", 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eDj300KjzY10rOFEBERABEQgRoJzyfXx0mzZtms2YMcO+/fZbdwZk0llnnWWXXnqpde/e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\n4avK8Xt0STm5XHbTI13H+n7flR8qr/zwoo7fAeX7l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xYsqJ/cfvvttZylCZJ+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BqeVAr3hOkJ8aQyYdIxzhOZ1SwmjIGLNVBEf79RYMZqns/7QUMv5IWNkbvXQisE6bMkHxBO4i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A/xa/sRaWPeloux4iPeSUvSEJ5vbG3QniM/Af1wT71PfOO258tHAF5I+T5+MMP5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\nTYTi/0S+WR1ug083LIMdAnfw5A52Z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EM5bHC9yoIR16tcUj7yryeWc1Yw0LnxxFeXXY5b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sDH8mmLTlsqHOt771rbp7Zc18cPnBD35QnvOc59T1oKbdRShN3VL2hJ9snvbB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\nxS6ns2bNqn4R5hIgyg13K8B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9L8pfv3et8qos5TzovIFite0c2NrppQOfE6//S9n5jiPL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\n5YwfZ/3K9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Yo9mIBAQCAgEBAICNRXBMKIZ5Y1o48+QgGXRj412qnjVeCTYIDw8N///d8u\nh0mTJrmt8CUk4Lk7CgnCEcpVWFjo1oGtW7fOvvvd79q8efMSmwkRLmVTf/eleErIBcPdEccsm229\nZiuJpth+UVxiX1PKps3Sn6dYstKGNe9evvYzzxZtmWt9WlV+tKzTqxw1+NQAAb3L6g+hmgGiWSFK\nlnf0rbfeSkyl//73v2+///3vrU2bNu791TssqniNnQpDKBf4cR40O3ljfvOb39j555+f+EkHPvSB\nGuUUVb9I+O6GYWNvI+H5AgIBgYBAY0IgKJ7VqE0JB1ApnqISuBC+MPoTffPNN7udWfFDoECQUNju\nJiSAG0Y4rlixwk3B+/jjj+173/uePf300+7QeYWDE5eEK1GELLAjDBMELQdDI72VWP6VPW3QHavd\n8z26ZpsN6+ztONRIn7qhPJbe1bjyKcUTCo/6Os7lHTp0qH322Wdu7eef/vQntzZe4Tz37vI+gwtG\nGP7zn/90azpZZgAGLNNgjScGfPGjz2PqLVSzbUR9DF2kcAsIBAQCAgGBgEA9QyAontWsEAkJCAIS\ntqR8su4TBVQCBYIAShJ/r6+//nqX07Bhw+z+++93woMvKGBvzEaYCD82zDjrrLPcUQFdu3ZNTMVT\nOIIVF/ghWHFhD0pnY24llZ+taP4E23/gJBcwedFGG9enXWWm4FNnCPjvtfpDqNbAa90nfOrvmN3A\nTq1FRUV2wAEH2B//+Ec7/PDD3TOIZ3frD1HEWaJRUFDgfrTxzTj99NPdN8bHjp9v9IH+Tzj1lQDY\n2HGrs4YeMg4IBAQCAgGBWkEgrPGsAYwSjqQYQfGTUIAbg8CAEDZmzBi3TgeBgd1uc3NzE0cL+IJb\nDYrSIKLoGcGC67bbbrNTTz3VKZ3HHXecEzy//e1vJ/78S5CSohnHWQ8dhCwh0Xjp100Pic6BvNEe\nXbQ+KJ31sJr1Dvp9InZ+FEHVJ2KnH+Dq1KmTm1J/6KGH2kcffWQ/+MEPbM6cOYlw8anfqIePXeMi\n+c+m/vBvf/ubMfUYpXOvvfayJ554wq15F6+w1cimqL47hGNEa1y4EDEgEBAICAQEAgI7GYEw4lkD\ngCUQQCU8aKotfvztj08xQ4lCsLjoooucwrXPPvu4kU+OD5EAQVEam/DgY/Xpp5+6Mzr//Oc/O9TP\nPvtsu/POO51wGscL4YrLVz5xCyMJY84j3AICAYE6RUB9oSj9ot8nploDzygfZ30ujs5mxdA3cvwK\nG4vp/W7M/SFYsXHQNddcY5zXyXKDhx56yI3+6rsCLnwf/BFO2fXdEIU3mIBAQCAgEBAICNRnBILi\nWcPa8RUqhARNt4Xi9gUteBEOuFjPiLC1bNkylzNb5rPx0J577pkQtghoyAIXzysDFrhfeeUVGz58\nuDs2hWflmdk0Q1OT4ZGw6Sud2PFHAfUFrIaMj7AJNCDQmBDgHdal95r+UAqo+kae2X9/b7/9drv1\n1ltd3COOOMKNfnL2p/jEK+oCGtANTGToDzFbtmyxSy+91K1rxz1w4EC766673Hmd8MOn51V/CFU/\nqH4RHvGRTjABgYBAQCAgEBCozwiEqbY7UDv66ENRijQ6h5u/0gonCwQJrv32289NLf3Zz37mcmbE\nr0ePHvbXv/7VhUtwE92B4tVJVAlZKj/HJvz85z+33Gh6Mef4cVwK5/ihdCKIik9YgSFClfDEHz+o\njG+XX6ABgYBA3SPgv8d6d6UwSWmilPSF6it+8Ytf2DPPPON2uGXn2549e7ofU1Jexae+ou6fMvsS\npCo7u/keeeSRTukEm1//+tf2yCOPuGm28KdSOv1vi37AhX4w+3oInAGBgEBAICBQPxAII547UA9x\noQKBAWFJlHB/cw2ykjCGIIECxojnpk2bXClGjBhhv/rVr9y5dxLgVLz6LmT4WFBm3JzdN27cOKdw\n4vfjH//YpkyZYs2bN0850gkmmkYmQQvBDCM86jsOrrDhFhDYTRHw+wHs/FzSqKdvJ4xL7zXv++bN\nm23s2LG2cOFChx6bjjH19qSTTkr8ePLff99e3+D2caBsuDk66uqrr7Y//OEPrrj8hGMToaOOOqpS\nfwgDfR8XiqbfL/Lc+GHqMwaugOEWEAgIBAQCAgEBD4GgeHpg1MTqCxjYUTq5tM5TSqj8yUOCA8IW\nI4LXXXed++NNWIsWLdyaHxRS7BhfuPDtLrCOb3p+ioGd6+WXX7YJEya46bX4t2/f3phOd+KJJzoB\nCwEUA68EKCmdPB/CFu640kmc+vb8lCmYgEBAoAIB9QlQ9Xv8kJPiCcUfKl76AV0cJ0L/8Y9//MMl\nesYZZxjHUrHzrd5/URh8e0Updr1Nz6KccXOhUPPD7Z577nHfBfo1+verrrrKLbHQz0rFAwf1f9jV\nH+LHs/qX4gQaEAgIBAQCAgGBhoBAUDxroZYkcEARqKBxIUvCBf4YCQ8SMljzibC1fPlyF84ur0xR\nHT16tO29996JOM5SHl/2uqB6ZvLGzrVo0SI3RY6RXAybhHB2KaMYnD0ngVNxeXaMlE4JWaKECSfZ\nocEEBAIC9RsBveNQX8mkD5ASqj5RvOoPULS2bdvmlLWZM2e6foN+gCNYmEHRrVs31y+AAP4yvl1+\nu4Kq/OQlO/Tvf/+7TZs2zSmcX375pStK//793dRaRjvBAj7wwaivk9IphRNcgtLpIAq3gEBAICAQ\nEGjgCATFs5Yq0Bc4JEwgWEjQIhuNghIufoQNhAqECy7WOnFwOGfdYRj1ZDOiSy65xA455JCEcOIC\no9uuFLZUZvKWnUPPGaFgrao2TEJgOu+889y0Mta0+hgoHs9K2X3hCjv+UIwEsV35jC7jcAsIBAR2\nGAG961Apn6JSOtVHkhl8vP8Y+gDee6an3nLLLca6SJl+/fq5n1lsyOP3FQrfVf2Fno98ZYe+8cYb\nbrdajs5iqQXm6KOPtv/8z/+03GitOzw8PyaudPI8Ujz1XQhKp4Mq3AICAYGAQECgESAQFM9arERf\n+MCOUCVBC7sEDvmLH0EJgUsX/k8//bRT5lavXp0oYd++fZ1C9x//8R/WqlWrlEpnbQtdKqMKIffS\npUvtsccec+eSbt261QV/85vftGHDhrlpZAceeGDSs8NAXAmWlFPrlvBD4NLzQwnXpbwDDQgEBBoW\nAuovoFwoXKLqB/HDjiFM7z1USteaNWvces9nn302oaztv//+bpOyc845JzENlzhxk8ovzpONm7LF\nDX5cn3zyieuzOQ6FczllOJ+TWR8DBgxwzwivnpVvg8rGc0rR9PtC7PD4l9IONCAQEAgIBAQCAg0N\ngaB41nKNSTiBIliI+goodv3xJ5zLF0CwS+Biow2mmz3//PMJgQuFjb/+P/zhD51Aw7QtjNJI9UiZ\nwuCnDOkMYSUlJe4c0nnz5rnNMT744IME+wEHHGAXXHCBsTnSvvvum1LhhFkKpa9o8pwIVwoXj8or\n6hjCLSAQEGhwCKhvgaofxC7FE+rbeUDC1RfgllL20Ucfuf5wzpw5xrnAMhy/cvrpp7v+8Pjjj0/s\nKq7wVDRT36Iyp4qHH+ErV6605557zjiXmLNIFYdlBYMGDbKLL77YjjnmmISy7X8PlDfPqP4QP/WH\nshOGwa04ziPcAgIBgYBAQCAg0AARCIrnTqg0CSBQLl/gQMDSNKt0U28RMCSQQHHzR50RRqa1rlq1\nKqnUKH7HHXec8XedbfpZA9W6dWvHU11hhfJSvnfeeccJVqw55QxOKOWV2Wuvvey0005z665yo+lj\nlJPn9C94SY8y6JkQrLhwS8jSM0IxKrOo8wy3gEBAoMEiQD+ASdUf+oon/Yf6R7/vIK76DfoJeFD4\nnnrqKbc7uKa0wsfacvpC+kT6w+7du9vBBx+cpMjCl41Ruel/UTTffPNNW7JkiesTfcWXtI499lgb\nPHiwDRkyxM1I4bmIr+eBh+ejX+PiOXimOPWfU32gKGkEExAICAQEAgIBgYaKQFA8d1LNSWCB6pJS\nJkELfwlaPo+EDAknCCayQ1n/OX/+fDcKilLoCzZ6HBTPDh06GFNe27Rp40Yi2aSIv/Ha6AdhjZFM\ndo/kKioqsvXr17vjT1KlSVpsjnHqqadabqRsko5fbj0ffv4zUCaegZFaPQfClYQu/OQPr+JiDyYg\nEBBoHAjQL2Cg9BUY+hn1G/SL2KWwyR8+9RHYfcWMfoWNiBYsWOAUUCi7yMYNfRX9ITtsf/e73zU2\nb6OPZHkAYaTzr3/9y12ff/65G03lmCtmdrz//vtWXFwcT9IpuCeccIKdfPLJbqSVqb9+mfUc/nOr\nnyM/zfTQdFoo/npW7JjQH1aCPngEBAICAYGAQANFICieO7HifIEDuwQuCScSTCRsyR8qIyFEAkuc\nojiymQVrLllbxAHsKI87atjUiHP0GD1lulivXr3se9/7nnsG0qaMeh6fKl8JTVAuCVdSOP3n8J8R\nezABgYBA40SAvgKjPgO7+kHRuDIKr+LBH+9b8JMSh/3dd9+1V1991V5//XXXH7JOnk3QdsSQZ6dO\nndxa0p49e7r+8IgjjnA/00jX77tVXr8fh4e+TT/bRElXirQovNgxoT90MIRbQCAgEBAICDQSBILi\nuQsqUkKTL5Bgl7CCwOUrcgheCveL5ytoCCy+WwIKdPv27e5PPQroxo0bbcuWLe7izFBGObkQbPjT\nzx9/Niri73/btm3dCCkjm+xGq3JTBpUHqktl9svoC4X+H3z8pXxSxnj5SUPP4KcX7AGBgEDjQ0B9\ni/oQv39RfygKj5RSxQMR+gv1GVBfWVP/Ah/x6QcZveRiiiwXI6UopPSH8NAf7rnnntayZUvXH7Je\nnWUMjJLSJxKO8fs/3CqbH0Z54FP51BdSLsopShzc4lO55SY8mIBAQCAgEBAICDQWBILiuYtqUgKT\nhBayRdjhws8XsnDrr7/iqZjwYxBMJJxA4wKLH6a48pM7njb+8oPqwl/l9MOVnih8EqgkBEJ9hRNe\nLpWXOH583MEEBAICjR8Bvy9RXwOlL8SoD6TvkXKnfohwxZedPgXj9zG+W3aoTKq+J56ueNX3Eu6X\nQ/7KF354cFMm9Ymyi6qPxO3HTVUmlSHQgEBAICAQEAgINGQEguK5i2tPQo0oQouEGAk0vhKqcAk3\nKi68SkOCSpzCix+CTTZG5YBXaYv6fqSpvPCXG0HKF6bibglYiuNT7MEEBAICux8C6mOg6oNkV//n\nK57igcrAr3TUN4nCoz4qblf8OPXT8+3wKR9RP23Ccauvow/EDcXP94dXbuwYeIMJCAQEAgIBgYBA\nY0UgKJ51ULMSWMhaQo2ohCoELQlbhMlfNJ6G0oLWhvDip6/0RMlDApNP5R8UTpAIJiAQEMgWAb+/\nUX9HXPo7LvWFchMmP/h14a+0RPHz+y7c1TWp0lKaUP9Sn4gfdl/pxI0R9dOobpkCf0AgIBAQCAgE\nBBoaAkHxrMMa84UZ7Fy+Yik/BKy4f1zoij9GPO14eCq3hCDCfLt48dOl6bOEIURJwFI83OIV9dOR\nPdCAQEAgICAE1G+p7/MpfSBGfZ+vhMouHqUTTxd3PEw8caq+DH/fLj71a+r/cKvfS+UnftF06Sr9\nQAMCAYGAQEAgINDYEAiKZz2oUQlCvpDl2ykiAhV+EroULn+fBzvhO2IQjjC+MCW7/P0/+fKTUKX4\nCGAy8pM70IBAQCAgkAoB9V9QX5lUvyfq94fqC/04ikse+NfE+P2W+jcpmAqjL8QuSj5xHrlVBsWV\nO9CAQEAgIBAQCAg0dgSC4lmPaliCkYQqiiZ7PAyByhe04uGKC/WFL9ypjAQqCUNyi1duqBROhUm5\n9HkIw+1T5wi3gEBAICCQBQJ+nwa734/5/aL4fCXUDyeu3PF0cKcz8X4NPr9PU3/nK5v4+fGIE3cr\nDcKCCQgEBAICAYGAwO6EQFA861ltS4iiWLKLyg+3hDDsuuJ+4odmayQUSahCaIr7kZb8/TDlIT/c\nvl3hgQYEAgIBgWwQ8Ps++NXXya408Kf/E7/s4pd/PJ7ip6Pqv6D+5SuTvj/pyK00ccv4dvkFGhAI\nCAQEAgIBgd0FgaB41tOaTicoyV8CFcX37XKnor4f9rgQJHecihd/P0x2hUNl/DD5BRoQCAgEBGqK\ngPo+4sftcvt9oe+nOPLzyyC/VH0Wfr7//2/vfaCjOO583y/vAI5wRCLH4I14MTjgBA+74BtIHtiL\nPVycGJycgSSw9o4gfpAMgfwBkdgHxH0XrtgXJI7jBZFs5CBHfrElbRyRONKxI2KLiwybiMQia+ku\niLWlRMq50m5EIjlSmHEsndOvev50V/V0zx9ppJnRfJszqKq76le/+lRPza+6qn4tx53Cumw5j11c\nLp9hEiABEiABEsgVAhx4ZnhLR4yiiJpy3C4cORf5q+eTwxE5dn9lYykStv7V89mdk8/byeY5EiAB\nEkgFAWt/Jscj4chfvTw9bI0nokekn9PT6mFrPCIjcj7y13o+EudfEiABEiABEsh1Ahx4ZukdIBtS\nehXkuBy2XotV3ViGU6xrsWTyGgmQAAlMBQG535PDetmReORvovpE+r3I30g+OS6HI9f5lwRIgARI\ngARIIJoAB57RTLLyTCyDKtY1ubKxDKhY12QZDJMACZBAJhCw6/fszsXS1anfczofSxavkQAJkAAJ\nkECuE+DAMwfugESNLRpTOXAzsIokkOME2B/m+A3A6pMACZAACaSNAAeeaUPPgkmABEiABEiABEiA\nBEiABEggNwj8H7lRTdaSBEiABEiABEiABEiABEiABEggXQQ48EwXeZZLAiRAAiRAAiRAAiRAAiRA\nAjlCgAPPHGloVpMESIAESIAESIAESIAESIAE0kWAA890kWe5JEACJEACJEACJEACqScwFsDQ0BCG\nRsZSL5sSSYAExk2AA89xo2NGEiABEiCBKAI0+KKQ8AQJkMDUEuj4ziO45ZZbcMvq72BoaotmaSRA\nAjEIcOAZAw4vkQAJkAAJJEeABl9yvJiaBEhgEgjMfndI6JLZmDkJ4imSBEhgfAQ48BwfN+YiARIg\nARKwI0CDz44Kz5EACaSDwHA6CmWZJEACTgQ48HQiw/MkQAIkQALjJ0CDb/zsmJMESIAESIAEpiEB\nrkCYho3KKpEACZAACZAACZDA1BAYw1B/L37T3YO+oRt45513MFusfJi/aBEW37EE8/Kzz9QcG7mO\nvkG/wDcLc+fPR0Fe9tVhatqepZBAcgT4TUqOF1OTAAmQQEYRCAz1481/70b/wBD+bBh8d+LDdy4W\nxlJGqZqQMjT4EsLERCSQAQSGcLH2NL557CAarzqr4ympxj+W7MDifLs0Y7hU+yQar/wJyzz7UbRq\nFI1PP43nmy7jzyL5u29bhk/v/CK2rF5olxlD3RfxfO2P0XT5N8Hrty1bj51f2YH35t9smz6hk4EO\nPDp3Beoiid2VGD6/G7bqR9LwLwmQQEIEOPBMCBMTkQAJkEAmERjB5cZafPfEt1DV4mzxeUvr8cSh\nLSi07elp8GVSi1IXEsgmAmPXL+FL89egKgGlG8t2orGsGa2DtVhdYM0QwOtPH0RZizhfdgU/dDVa\nBrGNqKsqg7e6HbU7liuZe88exaKNR5RzaGxEVdk+9VyysbHR4KDXyDbXCDFAAiQwQQK25sgEZTI7\nCZAACZDAJBFIxuCrO7IVdUd8aBs8jZU0+CapRSiWBHKPQPs/l0UPOl1ueO+9E/j9z1EXNQVahzVf\neQj+2iJYF2LcZAzsIoNON0orP4eb/v0nOHiyMQi3buc+7N58Hmsj/dj1s3hIGnS6feX4wv15+Omx\nfahzfhaXWEMJyzjsEzeUnvvVE+PGVCSQAAE6F0oAUuqTBHDxqaPYtX8Xjj5zEXy9ceoJUyIJTFcC\ntgafXlmXy6HKVVj1fz+DEZur9gZfNcqLPUZq3eC7KL8Iz8bgq6mpgNepeENSAgEafAlAYhISSD+B\nWbNNHTzFFWjtGoB25TxqT59GbcMV+AfaUWp2I6HEddvw42sBM6NdyF2OLv95HN69AwdONKC51B1O\n1YJ//Y3Zi13+50pExpeeilacP30ARUV7UXtlEPXFqeiM7JTjORIggYkS4MBzogTHlX8MV54/gqqT\nVTjy7L/aGoTjEstMJEAC057ArMjrSvSauotRf6Edg8Ojwui7Am10GJ3N1XBbKTTuxJkO02izXg7G\nafDZYuFJEiCBaAI3F66ES/Q/zV2DaDixF6sXz1MS5c1bjsM/aIdXOQv88UasR+3F6HzlABZLU6Lr\n9xxAZBj5y46+sLQRvHYuNBMK+HD8S6ulUgqw5cQlVKfkSZgklkESIIGUEODAMwbGwPVeXLt2Lfjp\nH4nVWcYQYnspD/mF4Qtz8/Eu2zSJndQdcfT29opPP4YCqdQxsfKZigRIYGoJzA46zXChoqkTo+dP\nYMva5SiIeI2cmY+l63fgp501UUo92/JG1DnzBA0+kwVDJEAC8Qgs9hzGFdH/rF8cWftqkyNvOb5W\noU57moNHm/SeD2OBdQPYuwtxdzjpn0duhEKBPvw6Mu50fyQ6j3ADtOaBSC6bcniKBEggbQSsX/G0\nKZJZBQ/h7KkD2LhP2jafoFezsaFreP65H+Kn58Ie2d59G5Y/8Ck8ssWDhfljuHzmObzW34E9EXdp\nXT/Bqaf+gjzhjTKAQmz/kpMjEBtC9LxmA4WnSGB6E1hadBpaUew65i0tQlPJMWwsiyxGA4xtVHZZ\nYxh8uoSkDb4Jb7KyU5LnSIAEso3AzfnKbkl8+PYYPZHtXsrR6CqP3cDvw2fdn77b1tvsO3+JzpaO\nM2NDvWi9+C84f/5VXH79TXS1tISWCIutEe6778UGYR9u2fwQFheo5nj/pVo88XxbSOWC5fjK48Ir\nsDQTbFeXke6zOPHtnyG4M0LkKT60AwtVseFsAVy7+BJ++OMXcP7l19FyNfw7oe/R/cQ6fPozf4dP\nrl0atRc3UqbuZ+DJY8/jP8WJvDvW4fG9HhSM9ePMk0/gn559OSRPyPI9/GV84/AWqHPhESn8m6sE\nbG/JXIWh1/t6RyOKV2wy3WhLMOLNJwa6G7FqySZj30Eka11dFQ7+pBojDZvx8yM7sc+0BYGrjTi4\nJ/LozoV7doiBZ6I+u+l5LYKYf0mABCwECm/Xn/jLnY0lgRylwWfQoMFnoGCABCZIIIB/a31dkfHe\n98YZPSmp40daftkttiutth18xs89iSkCvaj9h73YVhax7yxlicGePuBr0e3DnUDlhT7sXhtZCgf8\nx6+exsmTLUamG4vvw+mixUY8OjCGnx3fiCPGfIkbn9kvBp4WezLQew77Fj0Q7RhKF3i1RThmEp+T\nwlOwqxitLU9g9bzoYULgd78STp9OhlUYgGfLIrz88RU4Iv/cCDlVQszO/WLgadEhWneeySUC0XdU\nLtVermugX3QSe5ROQt9XIH+PYsMK4MeHzUFncUU9Hv7YbRjoPI8TO4+gpesv0ETX+LHHSlHy5tu4\nUlaGUHfkRknpOrHc9m0MvX0nbk+mTxYKKc8SbY1HuZIMkwAJ5AyBmya3pjT4Inxp8EVI8C8JyAQC\nHT/A1irZivLgv3wwxtJcOXOscP6tWCkMtKDj3P4/2jpo/NOf+mNJmPRrHd+PMei0KX3PfR/HooEr\n2BCeHnR94nMiVYuRsurpl3BcOE9ypDfSjueMQafI5loX9d7UQPcZMTmyVbFrjQKsgasnsWb+gP0r\ncGTPUmKaZs2CyBI+q5A7MSe24WzNwHgOEOAeT9HI+hPudXMWKINOve317jKyqV2Pxz7GMKK/7Vgc\n7vJWnNi7BatXr4Vnx2GcFw4/Bv7lUTHsnInVIn7s2FFsjmx78HwO//3wYRw+fAwnjjktiwjJ5f8k\nQAIkkBiBAN6wzDS8e/asxLLGShU2+IJJppHBd/a6WemQwWfGdYNPduprXgmHEjX4nGYZrAKDBt+j\nuGRXaJTBZ5llMGTR4DNQMJAWAtcvn8FDK8RUnnS4yx8zX4cinU8+OB+L7w7natmHn1o85erv97zv\nYEvyYlOYQ1kg7PKioqYJnT19whHcMAYH+tAW5QTuKr5eec7QIG/pgyiVDdCW7+Jir/O6u+u/eik8\nmRES4X1ss9i8JR1j3ThkHXR6y4U34j74RzXhmM6PnrZ6izMoMag80Gg7sA9KljypR1R1+0pRWVkO\nn0c/cwOjzipLyjGYSwQ48BQmxZmSbdJzJdH87lJcaGsKfgHlZ3Wxbwzx7QrPOLYcrMa5XslluHD4\nMa9AnsqUrg3/Rcx18iABEiCBFBIIvIkXlJkG4IF77khBATT4rBBp8FmJMJ5LBEZ6L+Ps2bPicw7n\nxN/aZ05h16ZlmL9qa9CuMsYmnkr88MDaFKHJw98+XGzI2nbXF3C2QzhYFA4hG0/twiLp/Z6xN7cb\nIlIeeK/w+guXB5XNnfBfqcXeog1YurBQOILLR8G8QqwUTuBe6WlQJjeunn9TestBIf7uMa+k11V8\nr6ldisvBAF4Vb0owDxe2PxgZCobOdv/kOCKLY/UzruJ68U7VA8IbcSHy9FnJmXlYuHILav2dKJGz\nVpXgVenBXEha+P/g3tBQYt1WLm3qEq+1OYzduw/gtHilzuhoLVZyma2CjBFBQMv5Y1irdItVsAKF\n+CpqFQ3t2qjOZLRdE5OS4fPir7tSG47D6kKp20wv8npLKjXxbiubXMNatScsOwG5NgJCp/xtmuiW\nzDInIsuxEF4gARLINgKdNT6zXwj2EcVaV7Bjk2sSpx+S+hdPRZuRsaehWJLt1Zra+7TBgR6tocJS\npid+n2kIjQSkMoN98jj6tK6GUk0YfJow+DR/RK7l72hPgybMJbMelnI6q73mNZHOU2nWXxXl1+p9\nkhzxG9LUp4Luqle5CIPPXi9/pyYMPqlcl9Zs+fkYbq9Urod+t6AJg09Ra1RVQbnGCAmkjoBsP8n3\nrhr2VFwI2VW2BQsZkj00aE0j9QlyP6RpfZqYEZS+Dw7hNPVD1mrYx639h09rlzutgWa1n3KVilrb\nHMOtqr0aVecerUTu7+BVy7GIHLxQrnD1VrcrKdR+KMTdmkbJwAgJSAQ44ymWvy7a4ENxRQN6/Few\n17NcnBHH6Ki6f1I/F+dYe/iHqCl2G6nqyvZgzZL5mLHpODqGMnu9ge557WJjLY7u34VN69Zh2YwZ\nmKF/li3DuqJdOP5MI7pt6qAvU96/f3/oc/QZdEuTuQYIS0D3vHZUyuO8ekT3vHZGpC3COqFHUJ+g\nTutQtP8ozly8JjwBOx+657Xj4XIOnWoMLZfTPa8d32/KW7YOu46egdMDPWfpvEICGUpg5DIObJM3\n+4g33dV/BYtt9trIjh8T7aEWeh6XloDVYeOKBbhl/iJskr2ApxGN/poH7UoDdq939so4c+HHUeqT\nlGz5NX4rdSZLP7VTmYlo/NZL6JeSG0HrMlvPV3FvoQy6F9/bKreFF/98bIu9t8i8pXj8qXJDtL7Z\no/rFDiluDYbW4wiDD4c3qE5HZsoqWLMxTgJTTKBx3258SfzO9jt0MsZ29Lk3hewvRT9zi8C7880w\nxELSw5c6UeFzK6n1DVKl9e3Cv0ZN6HxG+77Iw1+vkWc1fw+/zGjex3BIvnz1CH5mWVasV7L/543K\nMtviz29UnC2Ndb+GMomSu/yrWC4vwpOu6cGCVRuVJbd//ouycNiSWkS91Xhqx/Lo8zxDAnYEpEEo\ngzIB6Smb4JbQjGck+0DnBa2i2KM8MQLkGYc4Mw0RQfH+TkBHQ7S/R6spserq8ORQcBCe14yseqCt\nwq3U01ejPnlXEgcjo5YZArd2wWYq2d/TrAm7UJEdbAfrOVex1jpg/3h/uK1Cyu/VWvvaHZ6QurVW\nGx2idecZEsh0An6todgl3ffiO+T0lFys4TBWXniqo1d0+NuNFRVRT7OHOzVh8KnliNk+YfBpwuAL\nnbfMIiZELhV9WkIFaZo6q+mx9AHDWo1X7X+qO+WpiFAhfU0lCoPihh6l9NGueuW62P+vXI+KSMz1\n/s460xo10+C1abcooTxBApNHoOdCtVZSUqKVlpaKT4lWXOzT3I4zkT6tLWpKU9dtVPP7/c6zoqN+\ncd3+d17P7R8e1Pr6+sRnQJOTjeoynbPpWe2PSeyHRoVCel2Hxccv6tVaIdtfHq3NYosMNIsVHJLd\n4y69YNHZb+mrrH2Zpg23ySslxGq8yguCVY/W1dUV/enp0Xo6GzS3VKarpElpG2s/VGFV2qIhoyQg\nE+BSW5mGHE5BxzM6IAY6kSUk4ktcYfS4ssE3juVoET1ToGN7pdzpqYaW3NmZYbGUTFr+5e+sVjpF\nuCs029+ViM7DbeqSEBuj2C+MNWUZnNQBmnrIuopBpU2h1s7RPq8ux7K8JaIr/5JAlhHoqpeXwYa+\nI9WdFktGqRMNvlC/QINPuS0YIYEJEhgWD3qri92qfaD/lts95JpgWSnPngLbytDJ36ddaBCDc583\nxoA81FcD0f2QZnkYpU5iiFIGLyiDRLG8RRkk6npYB57OtlBED8tfi11nta1M29aoNQMk4EiAS23F\nNzBVRyAgr5EQe7XnLcfh49WG+Pfd/C4jbCxxS/MyEGUBBT2vGe3DAAlkG4Ghy09hyVbZfYR4pFLT\niR1LY3l3mIm8vDyb5W3h2guHE3lBzxP2NPLyC1BYWCg+80IOKoxsQma6l3uKV2RdbHwGh3bpS/Vn\nYNasWZgzZw7mis+cWXOwZl+jfaXCZ+fds1lZbtZy5Mfolrv4oTY8Lb9FwLcdq2KhFnLr9tyHBQsW\nYcmSJdGfRYuw6K5NiqO7q61vSM5G7NSVFbK7znMkkB4C+YXLsePEebRVymtFhS6NO1HbMZIepaa4\n1I4zRzFDvDHhvk07UVZVJ97bOQ4F8pZjp+Lt5yReajNdXvde/LHSZ5Rvvz+qP3/jtaZxFCxlEX28\nab1K5xkkgXEQSLdpMA6VMzNLoLsWc5Zsg6ekGoe/uBkrFuQjMHQV3/mHbxoKvyM5pTb2NLTswXfO\nurFr+Tu4+It+rNq8AcoWISP35ARCntfEy4tPHcej1j1RwvtayPPa+7BikfmO0qDntcPrw3sIQp7X\njuyMWGAhz2ue3cKjW9QxPs9rbSfkPVGm57WFq+5CWaQj1z2vfcOD9eF3YClFG57XrgZfkaN7XjP2\nRAnva98RtlvajWRFYUZIIDkCge5G/O2qPUomsTwK3ylaqpzLlYhu8K3YemRi1Q0bfHVGJ6MbfIex\nd3XoTXo0+CaGl7lzg8DK3U+g9Ft1OBL5rRbVbvrFG9i93M5GmD5MrtXux4pt6oNAvXYujxf3fnA+\nbhUP/CC8VLSWnVQGjnYE7nnkMaDMfDXNvud/iS+t3iAGmCP4n9+Ty/Bh05poI+jWwmVCrPmgzVNS\ngc23z4YxAWJXaPjcO7gJ93o+ab8vPUY+XiIBJwIceDqRSfL8LPHl1I9G0Tnon6jDU40txsxDPu7b\nLnYwNoacThzceBcOBjN40e6f2oFn0BFH5J2iUUqHTkQccRg+MsKOOCKb00OOOOqCgzo9R9ARhxh4\nFlrlTYIjjrL7QuQijjjWO25wpyMOa3MwPj0IjPWfwyNLzAdDwVqJVxe0HNMNk9w7aPDlXpuzxplM\noBCbv+rBkT3mwAfvZLK+KdCt/yw+axl0+iqb8Y1H78c8ywqSa3cO4C7jwb192XnLQ+/0NAbvJ59D\nu+jfV779KzwrYXWVPoylNp3+/EV3KoLXP+LDjogBp1xhhAQmn4DNLTr5hU7HEmYufhDNlSXYu6fM\nGIBF6uktrccTh7YoXsYWbzmOmpI3sa2sJZJM/J2P2VIsc4Jhz2tiqUjosPe8ti1yOeh57XGxxE91\nmzY5ntcOIlIsPa9lzh1DTaaIwNAlPLrgAelZtijXXY6eH+1G9HPvKdIpncXQ4EsnfZZNAg4E3q2c\nH1Zi0y8y8ocexQ70VrbhtO0qMOCdRKYdxWP8zeKdnubKsjq81P5tvP+tF9Ei4Xts88ekmBkcG1WX\nNr8g3ge6d/lqMwFDJDCFBLjHM2Ww87F+9zFc0UYxPDgA4WFNfAYwPKqh9vAWm+WzBSg6dh6jw4MY\nEGkHBgYxqp2AZayWMu2SFTQ2NoZAIIAR8QmMBfDWyJ8VEbJTc4gh9Sd2lirXn/1hmxLXl5Scf052\n6O3Bw+sWKmkCb/1BiRe+ZxT9/b3o7u6O/vT2ore3R3nFQdfvrkuLmRVRwUjF19TBf3QKniGBLCIw\n0oFdt6wxHrwENXeVouuVA1iYo48U7Q2+9VGzDDqrZAw+867QDb4h9P9y/AafKYshEsgFAtfR9Hzk\n8XCovms+dOu0rvhvL19U6rf2ng8pcTWi2lbqNTO2/MHtyiuenq8+jaefe9lMgFL81+X2m8zzb18G\nt5Sy5WAjeqU4gyQwlQQ48Ew57ZnIL5hnONzIj2MAzhTOOeaJjdvz5hWkd1kcHXGk/E6gQBKYNAKB\nazi0egXkN0QCJegUexDt3tc5aXpkmGAafBnWIFRnWhIY6z2LomWbcKrxchznV8C12mM42KJiuLPw\nFvVEpsfmCj8QSeh48+ybldQDf3pbiUciQx21+Ht5CXLkgt3fwnvxmLQt6mrVQRypMzfOeio/CfVR\nviREvA/0c14pLt7q+Y1nOuQTjmExB8GDBFJKgAPPlOLMTmH0vJad7Uatc5TAWC+OPyQ51tIxuMSg\n038sY1ZMpKxlaPClDCUFkUCqCATEUtK6q43Yt2kV5s5Yh+PPnMW1/iGYg5QxjPRfQ+3RTbjLstcR\n3ho84jAzlyr9Ui6n63f4xeXLuHTpUozPNbGuK3TM/5uPKCocue+/4dL1yFX9UgCXhQO0W1ZsU5bk\nKpmiIgT2FfgAADivSURBVPl4cE9J1NnQCRc+v3GFwzX9dD42f61CuV61cwWKjjeifyR6ZDlyvRvn\nzpzCpqA38P2qN29FCiMkkDyBZB7iJC+dOTKeAB1xZHwTUUESkAgEcOZLi6JmEEqf/Cxm9XagI4bT\nDvHictz6wRVYWJBF3X7Y4LtZ6O58vBcrVi8Nel20M/g+MVCB1fMi+811g+8JrErK423Y4GuUtwpE\ntEnM4NtZty+SAbrBd2OgAU986SEUWpbE6Abfr159CaeO7EPj1WJ0jZ7I6RlsAxoDmUVA2WvTgoM7\nxSesocsl3sItPMmbc3Gy6m40nyzKCg+pygLYq2V4YJXd91+uG1Dd6Q/6tsi/8x4I95HSipQqrJlf\nBW9xKT5cMITzR+J7slUlh2KF939WvOKpTN1eoV9yfxFr4+yvKFjpQ71vHwwnkSJb3cFN4iOeW7o9\nuPfO24Abv8ebrzdaXvvyG+hj5sX2q3hDivF/EkiGgOMbPnP9QipfIDxZLCeqY1+TJn4ilBc8C89r\n2oB/NErjzmqvlM7mJcfBHH1aqUuW59Xa/OLCYLPygmNXaXOUfP2Ev71aKgNaRbueefwHX3I8fnbM\nmaEEhts0sdpK+Z6I/j7xuKdGm9i3apK5iD5tPPUTBl9IMfGydWHwRfEQBp9WWlqs9EMqN6c+LVxf\na18bKcPyYnV7On6t3hetk16+MPg0n8+n+bwem5fLe7TWYVUi+zSVB2NpIjDao5W77e9p9Xslp/Fp\nzT0Z3fuYMEU/IlamRvUjznXT07q0+i6zfoOtFQnl95X4pHTR33lTqVCoqcQlpQ/p6KvvsiZziA9q\nNcXuqPyx61Wi9VhMQvZDDnh5OiECXGorvnG5etARR662POudswRuC732KXPrPwuq/8tENHUhPzID\nI969ebxVXVKmS6g7eQRHLLMMwuBThMeaU0XeSmxXXuIeyur78icRequnIsoSycOW04MQBp/lvJgY\namlEVVUVquqsswx60mV4f2SiNionT5BAGgnMXIgD5/3ovFCPUp+08dBGJZfbi4r6Vgxqp7F+YZbc\n0Hl34uESt01tYp1agtvmmvUrWL0Xw13NKPaIx/t2h7sYDW0DOH3sa2IWM3LchjlxFqTc/7nHIonD\nf93Yvn6x5ZxTVDi1PHEePa31Qi+3U6LgebfHJ9qtGX1iC4d1MnXmbPV3JH9WHKVjlsSLuUaAd0uu\ntbhU38lzxGG+01P3vIYbL0ulxve81hJOHfS8dmC184Z5SSqDJJATBPLfj/XCzmtsHF9tPYtvQ2SM\nNj4Jk5wrbPDVKa+ZilemncG3DIe/thcnG20W/OkG3zcPwbPyj7hRVhVetpagwae8ozl5g+9vHz6D\nk2X/JPRqcayUbvB9evvD2PLJ9VHe0GnwOWLjhSknkIela7fgsP75TgBDAwP4/fCf8M47IUVm3/we\n3DZ/PgryzcHYlKs47gLz4BFvHdCOjVtAMGP+4vU40XAFx4auo//3/4EbQTazcev7F6BwXmTt6jx8\nf9SPpwJjmJmXD8trPqMUmCXSKIf3C1gV/+mXkmXh6i1Cry14IjCEgf5B/OHGjfD12XjPre/DLfPn\nwbILQMmft3QHRv2PiDceCJ1n5iEvntJKbkZynQAHnoneAXMTTZjGdELHZBrU3vOapVMT1RmP57Wd\nYcM46HlNQpKI57UWw/O67nntEZzesVySYB/UnRrMTKby9mJ4lgQynEAh9jZo2JvhWo5fPRp8NPjG\nf/cwZ5oIiMFHQeFC8UlT+RlebJ5408Fi8XE69MFbfrTpZZu89fv/pJwv3blu3HtmZ+YVoHCx+CgS\nE4vMzBM6J5aUqUhAIUBTXccRGMH1P8vurmdipv8tKJvLxZO8gaEhvG26bcPMd89DQSY9zKMjDjri\nUL7ejJBAbhOgwZfb7c/ak8C0IhDowFNHWqQqebH5nvEMGyURDJLAFBOYoe8EneIyM6y4AGqL5mCb\nMcuWhHqeagw37EjfU5/AZWyaswrJrrqLeF6D6MR2zbG+CxAJeF7zoG24ASudHncJvYqEXlFI3RUY\nPL83zp4o4bVz1xzF81qkRWJ7XvOgVei0WtJppOMpzF2xJ5IdFW2D2LsyyTUpRm4GSIAEcpaA6CuL\nRF9p9mletPtrsTyTHjzmbOOw4iSQGwT6zx7Cgo2md11XSROuHNuQG5VnLacNAToXwtvifVPjbM/b\n8pNa2jrOUmJkoyMOEw4dcZgsGCIBEkglgf5XfyANOvXXpm7noDOVgCmLBEggDoEhNFaag0498Vc/\ne2+cPLxMAplHgANPMV+5aI17XC3junn2uPKlLBM9r4Ge11J2N1EQCZCALQEafLZYeJIESGDKCIx1\nn8MeZXlbCTY6LjubMrVYEAkkTYBLbZNGNn0zBGJ6XgPGxgIIJOh5baz3DGYt2mrC8tbAXzu+F0eP\njdPzml74WEDoTM9rZjswRAIkkBSBsW7Rly2R+jKUoEe4u1yYlBQmJgESIIHxExjrP4dHP74X/cJT\nMDAXnz7wj9i7IdHXqIy/XOYkgVQToHOhVBPNYnl0xJHFjUfVSYAEJoeA8Pzodbkkg+/zHHRODmlK\nJQEScCAws3A9aq9ccbjK0ySQPQQ445k9bZU9mtIRR/a0FTUlARIgARIgARIgARIggSkgwD2eUwA5\n14qgI45ca3HWlwRIgARIgARIgARIgARiE+DAMzYfXk2aAB1xJI2MGUiABEiABEiABEiABEhgmhPg\nwHOaN/BUV4+e16aaOMsjARIgARIgARIgARIggcwnQOdCmd9G2aUhHXFkV3tRWxIgARIgARIgARIg\nARKYAgJ0LjQFkFkECZAACZAACZAACZAACZAACeQyAS61zeXWZ91JgARIgARIgARIgARIgARIYAoI\ncOA5BZBZBAmQAAmQAAmQAAmQAAmQAAnkMgHu8czl1mfdSYAESIAESIAESGCCBAL9HXjlF2/gHSHn\ntr++H2uXzpugRGYngelHoPfSObz2v4dExQrw0QfXY2H+9KtjvBpxj2c8QrxOAiRAAhlMgAZfBjcO\nVcs4AjT8JqNJRvDUurnY0xKW7a2Bv7YIeZNRFGVmBIHAtVqsumsbrga1caGmsw1FS9nisRtnCKeW\n3YJ9IWhASTO0Y+tjZ5mGV7nUdho2KqtEAiSQKwRG8P2iFdi0dSu2is99//AyAlLVdeNg2YwZmBH8\nLEPtNfmqlDCtwQAaD20SOi4L6rrp6FmlDsmrlmp5yWswFTmyo22ngkQyZQyh4fMPBL8rW7c+gEVl\n55LJzLQOBALdjeagU6Sp/NpDHHQ6sJoup8feGQkPOvUaXcUfb7w9Xao2ifUowCcO+Uz5Zf8vzl03\no7kS4sAzV1qa9SQBEph2BOIZfJNhHIz0XsTx/buwa5f47D+OS/0THcyOof9Ko2ibq0FDpvF8DyZm\nwqRaXmbeNpPRtplZ01RqRcMvlTRDssbw6rePmWJd5fjsygIzzhAJkIBBYKlnJzxGrAWnfnTZiOVK\ngAPPXGlp1pMESGCaEUiPwXflB4dx8GQVqqrE5+RBfP659glzvckiYaLOB1Itz6Ieo1lMgIZfihvv\n+qs4fjKydhDwHdqCrN3dGRhCb/c1XLt2Db3XR1IMKo3ipmu90oh03EXnr8KeYpeRvXHPj9BtxHIj\nwIFnbrQza0kCJDDdCKTF4BtB5y9aFJL3/p/vVeKMkEBGE6Dhl9Lm6XixGi2GRDce/sRiI5ZtgY6q\nz2DRkrtw1113YdF8Dy5Pk7HndK1Xtt1fIX1n4v96+IuS6mV46bLubCh3Dg48LW2tO+poPHMGZ8Tn\n4rUcXHxt4cFodhLQHWjo9/CZM+fQO01+PLOzJSZP6/QYfPlYvt6tVOrNP95Q4oyQQGYToOGXuva5\njqZv1pni3A/jI1k73SmqMbvQrAvmSuEsD07XemVpsxSscMMr6f7dH/1aik3/IAeeShvHdtShJGVk\nSgjQgcZ4MNOBxnioZVee9Bl8K7b/f2iur0F1dTVqGi7gh19amV3oqG3OE8h1wy9VN8BYbysOmqts\n4f3cPeIlETxIgARiEsi7E5+WfAxdLXsR3WMxc0yrixx4Ss0Zz1GHnjT1jjUkBRiMIkAHGlFIEjhB\nBxoJQMrqJOk0+GYWLMT6LUXYsWMHijxrMW+iGzKzuiWofFYSyHHDL1Vt1vvai4qoB9bcqcSzLXKz\nsjn83Zg1Td4OMl3rlW33l6lvHj76qWIzipN45WruLE2jyWA0fWKOOkKONVqMXD//q/tx5cBqI84A\nCWQCgZADjSrovkIhduDontPW7+bMVCa0TSp0mG4GXyqYUAYJJE4gbPhVnQxn0Q2/o1i8PAff5p44\nNEvKAC69UCWd82HNkkRGamPovfwqml56EU3nX0Zjizll6nJ7sGnDZmzc+CDWLpeXvUrFhINj/Rdx\n7IkfI7g7rmA5vvL4Dix2LH4Ml2ufRE3bfwZz/9W92/D1LSuhG8BDHWdxuqkd73lPHp7fIy0bxut4\n5slTuMOQKbx3598jHritReQuGeu/JHR4PqhDwfLP4HFxTU8+1HsZP/l+DZ59/iQi1XO5vXj4c9vx\n6JYNWBgREK6L/CcT6iXrk4rw2FAvWi/+C86ffxWXX38TXS0tQQ/mcLngvvtebHjgU9iy+SEsLoge\nkvRfqsUTz7eF1IjbzqFkI91nceLbPzPujeJDO7AwSnQA1y6+hB/++AWcf/l10U7h+9AllsF+Yh0+\n/Zm/wyfXLnV8LdDY9Ut48tjz0O+ovDvW4fG9HhSM9ePMk0/gn559OSRPyPI9/GV843C0w60FK9bB\nJQackbu/6RdvYPfyHLHRNB4hAgPNmhvQxD0U/PhqumzIDGvVHjONntZX02mTLkdP+Qe1nq5OrbOz\nU+sZGE4JhOH2SqNNdN4VbYMpkTv9hYxqTcUuiV2JZndHT38O07GGfq3GK/dDPq1z1L6e0d+f0Pdy\noLNZqyj2auJ337hH3J5irbKhTYv3zR0daNPKS4q14mLxKanQ2gYcCg+r5B9o1+orSjSP27wfXS63\nVlxeo7UH8/rVftVdGVOHVMsLqenXOi/Ua6WCidtl6gmhp7e4VKu/0Kn57REHz44OtGrlOg/xKalo\n0CK91EB7szg/Ps4xigteim7bSKnROUcHe7QLDTWifj7RDm5N+FQMtbuoq9vr08qrG7SuQft27Gut\nCbW1Xr/Saq0rFohw0cNdTaKs8D0i8vTYip4Yc70oW+6jfVp9ebHZjqINfaX12oAFy2hPg8lB8PBU\ntllSMBqTwGinJuZsjP4DnuqY31tdlt5eJW4pj5zfGvZWxLzXhtsqzLJF3vJW5/tfE5pVyuW6Kozv\naFuFW5ETsQHt/7q1VqmDVHRwV4s+wq81lXvjyHNpNe2SEAtkRWaa6mVRyTaaUP/j79FqSjxxeJj3\nQ+WFvqiyrO1jb5vL2Ua1ep8pE3BrFyy4/T3NmljpGl8vV7HW6vD7praTV2vta9dKpd9T8/5R7xlD\nU/H9UXRI4Ptj5M3yALJc/5Sp314tdxZurdn6KxUuyfolcFfwxyrSCO1KB+7W2ixf9ki6ZP4m1Lkl\nIzCH0g62qj/MHLRPk8ZPwuCzfn+q2zqFYRTHEHCXpszg66wvifvjXtF0Qav0SYO9GAPPVMvT74jJ\nMELaBge0+pI4Bm0czvHuVmvb2n6/p7Hhp/OZkPGXw4ZfvHsroet9TcrDek8cW8jfo6Y3DfNYA4Bi\nzWmMltD9b1TEMmkg9TFWmy62XuogQtVBPODwSP1YzIGNsDH7bJ/GaKrMeA/bJ6deBrYYgUT0bK+M\n81sTxcilNVlsb39ntfob4jYfGtiqN9ymifdkmnlcpZo8nPV31SsPnGK3ty5HDCptnmlY6+8sx6e1\n2z6sEw9DlImsYq3TNp1tLbP6JPd4irsFSNxRBx1rBIHZ/0fPafZc0nSWDjTSBH6yix3oEYvAzMOz\nfrmx9Ms8ax/aueoubDwYWoBtn0KcbTmCJV94Bo47TmbNVrLmzVKiRqS38RDu2lpmxJ0C+zbehz1V\nYsGR+Woz26SplqcXEug+g1WLHoC8YNC2cP3k1ZNYM/9RXLLzfK8wqcOqW+Zja1mLo6jghXicY+dO\n6GrH9/diW1mc9pYk7bnv4zhrcebu+sTnpBRA1dMvhZawKWelyEg7npOButZhsbS0MGXM9SIt3Ncs\nWIEjkbVrkkrAnZhjXWo3cwE+Yr7JHWjsQJ9YTckjMQIj//GG2MRhHh8sfK8ZsYbGruHQoo1Kev0L\nX1rdhPauPgwM9KGzrRkVxXKD6EJOYsXXGzGZflc+tKkMNdU1qK+vR7lP7oR0/cT5mhrURD5N38QK\n6V5Wq9mCqkbz5nP7ytHU2o6uzjbUlIu5LeVowQOPP4/JvN1SVy9F8aQio3JqlxcVNU3o7OnD4PAw\nBkWbtzVXwy2nEQtPv155TjmTt/RBiJlE82j5Li72Ot8R13/1UniLUSiL97HNMBZtj3Xj0JKtxvLW\nYApvOVrFPegf1aCN+tHTVq94nAXqsOZAjHtQLBuKHJGQ21eKyspyiAcR4tINjNqqm49l98j3+29w\n/e2IpGn+N6uHzSlSXl9yI5rZ+Hir21MkObfEtFfKs8Yeznimvfn9liUnxVqX/UPWtGtKBRInoM7y\nQCuud15EHeuprKekUrvQ3qm1t4llkd7oJ/XVDo9frTJtZ9oGLyizIaH+1atVN7VqXT1dYtlnpfpU\nWup/Ic1GGFRSLU8XPNqlLhXUdfCWa8II0YQRIq77NWGEaMLtvfHbEKyHr0Gzfo2sTPR0wuQI5hsv\nZ6PuDgFrmXbt0CbPOLi8mjD8NGH4acLw04ThpwnDL6qdXKXNlhL7LEvIXFqD/drZYL6B5lKFl/J7\nmkLmemEGA2l5dIS7MP40YfyFZ6G8tr9HF5TZf492wWZmwwKD0TAB9fden5lzXuLUVeNT7gnAZzuL\npIvualDvHzFAtb3fjLYPf8/s7n+zsZxnBs00mtaprHzzau3WL7qcWIStOoT6OZdW2SrPsYUy9TWX\nWxiI2b3oZFEy01EvSzVto9a62+kZbEuXR6tsdt6qYF3ybtf/q+0Sa1m81ebRGZuN2FWv3oeu4nr7\nLRT+Tq1EWTbriloFqdbf/P0sbVJ/j0fN4qM4Rn+HcqMD4lJbcStYb0YngyvqruEJhUBXkp22ktkh\non654y07cRCSw6d7GoqVH7tKp3VLOcwo26oe/WPlbPBZvz8Rw6i6zbKeSeyBqpGXuwpjzlPRaovG\nKtPO4LDqCLHcKeqhx+iAVqPsQw4P8GwGnqmWp1fM2u+n3ghxaRPhbAtfOplIO0xnw09HoTJI3viz\n3ld297KEnEGJgMrOpdX3OK0TtD64gFbj8FArIr7ZskzdXX4hcsn4q7Z9PNsgsYGnWqf4D8+tOuiD\nZOf9m6Nag6WPtXtoaJUZ+56cnHoZkGMEktMzhiAx9FP3ZNosTRU+WCIPlIK/YZbls4b04Vb1gaZH\n9hfQo5WEH1KEfgfFgwWnW1YIHLygPihQHqCJ69b66zKtaQy9HAJWGbHb2kFIFp7mUlux2CEZz2xj\n1y/j+KH92L9ffA6dwuXr0XPourer4/p18Tl0qtFYlnS945w4X4Rly2ZgxozQZ92m/Xiq8bLzsjZx\nN+ue046G5R195qKxPEP3nPbM0f1YJ8lbtq4IR585i17HdXJCYFDmRUPm/qPPoDvmmg/dI9zxUJ2F\nHsfPXDaWvuge4Y4fP46nnjqFL+ysCwkP/h/yCHfq1CmEPsdxSugeRy0pf/JB3XPaxcZaUa9d2LRu\nHZaFGc9Ytgzrinbh+DON6B6Kbi/da1qwPXXGcVmE9NK9pkXaRM/jvPJD95x2RqQtEu20zGj3GcvW\noWj/UZy5eM1oT7sa295Luue043q7h+UJWbuOnhELxqOPkOc087zuOY3HdCLgQuGt1jWEsernQn3n\nJexYaX3Lez6K/keZstq18YXXjb4rlsToa/34ybfkvgCob3wci61qzpyHohNtaCjWlyPFOlItTy+r\nF9/bKq8H9eKfj22x92CYtxSPP1UuKXgV1S92SHFrUF9uNxWcreVGxxd7DkO70oDd6529M85c+HGU\nyisBW36N31p+D5Z+aqd6b3zrJfRHFyfeN2ZZZuv5Ku4tjDT8ZDLXlQktcxTGHw5vWKxoNzOignIW\nuOOetZYzjI6PwN24Y77h/lUREej4mbr82VMNz1L7tJGM93/+C5Fg8G/L2X8dZ1+kiJn0SEnTT1Hk\n6Bl5JtbuVJetv/zzNw1batKVy9gC8vDXa8S6EuP4PfxWM23ex3BITnL1CH52zdJJifz9P29UltkW\nf36jsQ1lrPs1yBs/3OVfxfIYt2HBqo3Kkts//0VZOGxoawS81Xhqx3IjOq5AnCLGJTMTM2XhYDm1\nKifhqEMv2LrMzc6TmppGLPGZoKMJRR49p0W3/wQdaFidC6TCa5qu5GQ4LaHntOjmz7Uz6lN50b/E\neGprfaJaYre2ywA4qHp+VJ4WG4minvRGPaUVTkeUp9MOckyJlhkR64xnquWJgkeFgwnxe2x83OX2\ns7uGjv52Zcmt1QPqZHA2ynYIWMuMageHfHan1aVsHsVzZyi9mBFXPClDs1sZ1NekOpMqbugxiks1\nc12wlQG88T2rGgrZ5K+w8yIiZ2A4TEB4TVdmJZ1nB/0Wz/QlTeY94YyzR13eLRzKRK3RsMiNff9P\nzsyg9f6Lu6Jo0DIjZ+MoxyozHfVybhfzSnJ6mvn00KhYf+r3+7Vh8fGLLQ2tFbITIvt7ybqE311q\nnQW3entX+7HhNvUNCd7KC1pfX4/W1dUV/enp0Xo6G5RtCK6SJmWLRXT9nVceqbU3Y1YZbodVRmaO\n6RFyeA6YiUPkSdIpWUcdijMD8f4eO8caShrd0YT69N+2JkFHEx/AcO0O4wmNkU6W1/Is9m36prKJ\n3UinBK5i2woP/qrvFaw3njhLCWSZ4rRtPaTkN82VIvNnB99/JZ1Ja3A8DjQWDVzBhvCkT8h5RotR\nB915xvGivSgwzlgC1qf6FucZeuqgAw3rJnaLGCMadFoygNbBWqy2Fqq0k9jkvsDpXrJxnqEXEHGg\nEfEvEnagEeeBs6EaA5lGYAz9v5Pnmv4slkQkruPt8xw9YwghM6F8z4cTlyun1J2OmC42AM/Ge6L7\nNDmDuPqBJeKEnEm6nmp5uujAW3+QSgAK3zOK/v5eBAI2MMV02cxAjzLD1/W760HsTj+gU8FZqUCS\nkbGxMQjjL1QH8Rv21oi4j6Qj+mctH5/YWSr8bBwxUj37wzbsOCzPGAZw/jl5TsGDh9ctNNJPNnO9\noIqvbYlzrxnq2AZe+NW/Y+9qvpfbFo5ycgQ9rS3KGadI/xv/rly6vfAWJW4fuQUfuFtcifQJLefQ\nPbIXMbsve0FTevYdey8ypg4zrd+s2ea16RwK9OPiKz9D04vNaP15nfFu02SqPO+ezWIG8ggiFlDL\nkR+j+9BacyXNUBuejlzUBfu2Y1WMn7u6Pfehbk/iGlxtfUOs2NvgbBcm80PsUOyaD73f4cr0Op3z\nS22T8sw2gbaPLCYTjiYgHHpAOPSAcOihSqzbiTM2ywfURPScpvIAlNUJ4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It3T8j5szw8\nTQbQ467GYJv6RMZX0xlTViJPORJJYxYS/+m3VR48FVqfKSAqZH0S5K2OrpNVpjdGvbsaSpUnM3az\nsroS6oxneKYwSrvkTlj1tD5Va1dmMaHFeuLaXumR6hHjqb5lFtXlK9fED4mUt1TMvzgcA+rMKPQn\nZQ5JEzkdr/6JyLhQKj/dc2vNA4nkYppMJuDvVGfWPRVttupa01XHnEKwPO33VEetvtALSUrmYKdW\nWSx/78yn/nD7NGEUBvXukZ/+eu3LDSZMtbygUDGf2lqvCSNE+o5LeoafygsjRBNGiNZns4ghKSbW\nWT8HzmHVHP8kWqYw/ETd5P5Lqpu7WBOGnyijU5rB9DnOoMvKWMsXzlK0C0k8tJ8oc10Xqw6x729F\ne61GmX2L8XsgZ2NYJTDapYlF9eb3xlUu5uoSO/zDA1pPV6fW3t4e+nR2aQODNl+uxMRp2uhwSF5b\nW1BeT1/0zej3D2vDfr9mmbyyLWHUPyjkdWmdnZ1aV1ePNjAcrVus32f/YJ/W1Snq1iY+et2GEynV\nRpU01MtGC9tTo4Ll8PCw5rdZYWbN4B8cCPEItnen1jegzo6PjoZlJYjJumIB3hrRsyZ/6O3cJ9rZ\nuA/bO7WevgEtkeZKpv6KZtYVI+PUXZGZRRFkka6Toqq/q8bsNEUHGm+5TayOJqJgImkiacVioaSX\n2opnHZp4KZLt4NO61FM3BuwGGlYdnQZIXU2WQadetu1SOH3gqRqY1XGWLZsMnENWPa0Dz64aeYkG\ntNIL9j97g+01liW5sQwNS5vIP6wi7Km0N/JDtRB5FYNGLP2tbneuoHRl1KbDjVd/KbtDcNiyFEld\nKuSQiacznUASBl+yP46JGGfJygwacREjLPjDHm0UjiZrFKZQXqS5p9IISYRzRC+nv8m0w3Q0/HQu\nyTAwOOa44WdwSEGgtdwt2VAuraHP5ocsBeVkooiJ/z5nYq2yQyf1gbqw/ZpjTcdkVp0GW8ul7wy0\nkizSPRUkc37gKTblSU96nQdVEdiJdDSJpInIG8/A09jT6PJpTe194ad3o1rXherofTu+eoenQDZ7\nprwVWmf4iePocI/WUC7viRRsIgMwh4Fnp2UQCE+51hV8BDWqDXS1aU3N7Q66mDSsoXgsrdcBn9Y6\nID/38mtt9TaDZ7GPINYe1L6mErO+kXoH/4ofVutif4vS1ll0nZu3vEHrs3mENjzQpTXXV2hiJYoo\nr1jrsvxmW+tnHXhbio6Ojnaq+7wc2i46I89kOoFcNvgyvW1yQT8afrnQyvHrONql7pW1W2EVX0p2\nppjw73N2Vjv9Wlvt9hh+DtKvrFWDUa2hWF6BktgKE6uUbI5zj2cSntkyZVU1PaeZLTFZntPG6zVN\n14ye08z2YWjyCKza8mVJ+FU8/7MuKc4gCUwigUAHnjrSIhXgxeZ7CqV4JgfHcPH5ZyUFfXgka3SX\n1M6Q4MzFD0I4SDSOum/+0PY9lkYCBkhgggT6X/0BZH/FrpLtWD7BffcTVCnx7CNt+N5J872j7vKd\n2aN74rWMmZIDT+EKYbIcdcQkL11M1tGE8JwGt3nfCklXLS7IQ8Kr2/4FGwqdd2kv330Swjtm9GHx\n/iE8wkF4hFPSRTv/EJcLP45SNVkwj6KqIiUFkclyoDFu5xl6nehAIwUtSxFxCNDgiwOIlyeNAA2/\nSUObhYLFq4lKyk29rx7BmctDZpwhEkgpgSE0Vqrvfv7qZ+9NaQmTKexaYzXM13e6cGD76sksLiNl\nc+ApmiUZz2yJeLJKJI15N8zErbeZMcx18rZmpqHnNJOFHposz2nj95oW1Iqe09RmYizlBGjwpRwp\nBSZAgIZfApByKknB6p0olxyX7jv6U8R43eX0YRPX/fP0qWqm1GSs+xz2mCM3oVYJNq7MzxT14ugx\nhJePSW/vLH5STA7FyTINL8/Q1wlPw3olV6WxbuyftQSGc2NXOQauHMA8ByljgQACY2OYOTMPeXn2\nM4qJpJHFBwIjEBKFvLwoN98jHU9h7oo9RnKxzw97w+64A0P96P/9H3Djhrh88814/4KFmJdvr5Mh\nwC4wNoLe3j786S0haNYsvOfWD2BhoereOZaOVpFjgSH09Q8iMDoqxOVh7vz5Qq/xrYVIhmVg6Lrg\n8R+48Y6u0Wzc+v4FKJxndkpjY6LtAoJ0Xj4cms6oyljvGcxatNWIC69p8NcWObz02UxmF9J5DAge\nfwg2lJ5itmD8Ptwyfx7iNVcy9VfKDlxG0ZxV5pKUCeivyGUkgwhcx/Fl83EwsqzAI+7RhvHdoxlU\nKaqSwQTGukW/uETqF4Xh16OJ1w1ksM6makM4tewW7It8X4qboJ3YYF5maNwEAv0deOn8/4K+guuv\nlq7D+pXT36Ie6z2LRx/6OvqFfTMwUIgnf/o0Niwcn50zbvA5lnGs/xwe/fjeIHNgLj594B+xd0Mi\nr1HJBFBjuHbup7j8n+L1Zze9D3/7yQ3IxduFA8/wvXjp+DqsOdgSjrnQ0NcOT4xlqlN5C8caeE6l\nHrlW1sWj63CftI9JeE3D4fXZ82M6dOk4bllz0Gg24TkNx7JIf0NxBmISyEWDLyYQXpxUAjT8JhUv\nhZMACZDAtCbAgWe4ea1PcYVnNtTuWJoRjc+BZxqaQTjPKJqzwpwtFK83bvfXZtEm8DE07l+BTcYm\ndp/Q/3QW6Z+GNmeRJEACJEACJEACJEACk0aAezzDaOmoY9LusawUnNXOM3Ti9JyWlfcdlSYBEiAB\nEiABEiCB6UqAA0+jZemow0CR84Hsdp6hNx89p+X8TUwAJEACJEACJEACJJBRBDjwlJojYz2z0XOa\n1EqTH8xur2k6H3pOm/y7hCWQAAmQAAmQAAmQAAkkQ2Ac7k+TEZ9taedh7yvtWCx5ZssE/2R5ty6C\n1+UyPKd96NZ3ZRvY7NI3r8DgHfKa9vks8dgYwZyPT5xqQI3kOS1yhX9JgARIgARIgARIgARIIB0E\n6FwoHdRZJgmQAAmQAAmQAAmQAAmQAAnkEAEutc2hxmZVSYAESIAESIAESIAESIAESCAdBDjwTAd1\nlkkCJEACJEACJEACJEACJEACOUSAA88camxWlQRIgARIgARIgARIgARIgATSQYADz3RQZ5kkQAIk\nQAIkQAIkQAIkQAIkkEMEOPDMocZmVUmABEiABEiABEiABEiABEggHQQ48EwHdZZJAiRAAiRAAiRA\nAiRAAiRAAjlEgAPPHGpsVpUESIAESIAESIAESIAESIAE0kGAA890UGeZJEACJEACJEACJEACJEAC\nJJBDBDjwzKHGZlVJgARIgARIgARIgARIgARIIB0EOPBMB3WWSQIkQAIkQAIkQAIkQAIkQAI5RIAD\nzxxqbFaVBEiABEiABEiABEiABEiABNJBgAPPdFBnmSRAAiRAAiRAAiRAAiRAAiSQQwQ48MyhxmZV\nSYAESIAESIAESIAESIAESCAdBDjwTAd1lkkCJEACJEACJEACJEACJEACOUSAA88camxWlQRIgARI\ngARIgARIgARIgATSQYADz3RQZ5kkQAIkQAIkQAIkQAIkQAIkkEMEOPDMocZmVUmABEiABEiABEiA\nBEiABEggHQQ48EwHdZZJAiRAAiRAAiRAAiRAAiRAAjlEgAPPHGpsVpUESIAESIAESIAESIAESIAE\n0kGAA890UGeZJEACJEACJEACJEACJEACJJBDBDjwzKHGZlVJgARIgARIgARIgARIgARIIB0EOPBM\nB3WWSQIkQAIkQAIkQAIkQAIkQAI5RIADzxxqbFaVBEiABEiABEiABEiABEiABNJBgAPPdFBnmSRA\nAiRAAiRAAiRAAiRAAiSQQwQ48MyhxmZVSYAESIAESIAESIAESIAESCAdBDjwTAd1lkkCJEACJEAC\nJEACJEACJEACOUSAA88camxWlQRIgARIgARIgARIgARIgATSQYADz3RQZ5kkQAIkQAIkQAIkQAIk\nQAIkkEMEOPDMocZmVUmABEiABEiABEiABEiABEggHQQ48EwHdZZJAiRAAiRAAiRAAiRAAiRAAjlE\ngAPPHGpsVpUESIAESIAESIAESIAESIAE0kGAA890UGeZJEACJEACJEACJEACJEACJJBDBDjwzKHG\nZlVJgARIgARIgARIgARIgARIIB0EOPBMB3WWSQIkQAIkQAIkQAIkQAIkQAI5RIADzxxqbFaVBEiA\nBEiABEiABEiABEiABNJBgAPPdFBnmSRAAiRAAiRAAiRAAiRAAiSQQwQ48MyhxmZVSYAESIAESIAE\nSIAESIAESCAdBDjwTAd1lkkCJEACJEACJEACJEACJEACOUSAA88camxWlQRIgARIgARIgARIgARI\ngATSQYADz3RQZ5kkQAIkQAIkQAIkQAIkQAIkkEMEOPDMocZmVUmABEiABEiABEiABEiABEggHQQ4\n8EwHdZZJAiRAAiRAAiRAAiRAAiRAAjlEgAPPHGpsVpUESIAESIAESIAESIAESIAE0kGAA890UGeZ\nJEACJEACJEACJEACJEACJJBDBDjwzKHGZlVJgARIgARIgARIgARIgARIIB0EOPBMB3WWSQIkQAIk\nQAIkQAIkQAIkQAI5RIADzxxqbFaVBEiABEiABEiABEiABEiABNJBgAPPdFBnmSRAAiRAAiRAAiRA\nAiRAAiSQQwQ48MyhxmZVSYAESIAESIAESIAESIAESCAdBDjwTAd1lkkCJEACJEACJEACJEACJEAC\nOUSAA88camxWlQRIgARIgARIgARIgARIgATSQYADz3RQZ5kkQAIkQAIkQAIkQAIkQAIkkEMEOPDM\nocZmVUmABEiABEiABEiABEiABEggHQQ48EwHdZZJAiRAAiRAAiRAAiRAAiRAAjlEgAPPHGpsV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"text/plain": [ "" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": { "image/png": { "width": 400 @@ -222,10 +206,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 5, + "metadata": {}, "outputs": [ { "data": { @@ -234,7 +216,7 @@ "" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": { "image/png": { "width": 500 @@ -264,10 +246,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "data": { @@ -276,7 +256,7 @@ "" ] }, - "execution_count": 7, + "execution_count": 6, "metadata": { "image/png": { "width": 500 @@ -338,7 +318,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": { "collapsed": true }, @@ -370,12 +350,54 @@ " return images, labels" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "**Important Note**\n", + "\n", + "Some readers experienced issues with the `load_mnist` function above as certain decompression tools renamed the files from *-labels-idx1-ubyte* to *-labels.idx1-ubyte*. To avoid this problem altogether, you the modified function above will directly load the dataset from the `gz` archives using Python's `gzip` module." + ] + }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": { - "collapsed": false + "collapsed": true }, + "outputs": [], + "source": [ + "import os\n", + "import struct\n", + "import numpy as np\n", + "import gzip\n", + " \n", + "def load_mnist(path, kind='train'):\n", + " \"\"\"Load MNIST data from `path`\"\"\"\n", + " labels_path = os.path.join(path, \n", + " '%s-labels-idx1-ubyte.gz' % kind)\n", + " images_path = os.path.join(path, \n", + " '%s-images-idx3-ubyte.gz' % kind)\n", + " \n", + " with gzip.open(labels_path, 'rb') as lbpath:\n", + " lbpath.read(8)\n", + " buffer = lbpath.read()\n", + " labels = np.frombuffer(buffer, dtype=np.uint8)\n", + "\n", + " with gzip.open(images_path, 'rb') as imgpath:\n", + " imgpath.read(16)\n", + " buffer = imgpath.read()\n", + " images = np.frombuffer(buffer, \n", + " dtype=np.uint8).reshape(\n", + " len(labels), 784).astype(np.float64)\n", + " \n", + " return images, labels" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -393,9 +415,7 @@ { "cell_type": "code", "execution_count": 10, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -420,9 +440,7 @@ { "cell_type": "code", "execution_count": 11, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -461,9 +479,7 @@ { "cell_type": "code", "execution_count": 12, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -507,7 +523,7 @@ "cell_type": "code", "execution_count": 13, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -534,18 +550,16 @@ }, { "cell_type": "markdown", - "metadata": { - "collapsed": false - }, + "metadata": {}, "source": [ "## Implementing a multi-layer perceptron" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 8, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -782,8 +796,10 @@ " grad2 = sigma3.dot(a2.T)\n", "\n", " # regularize\n", - " grad1[:, 1:] += (w1[:, 1:] * (self.l1 + self.l2))\n", - " grad2[:, 1:] += (w2[:, 1:] * (self.l1 + self.l2))\n", + " grad1[:, 1:] += self.l2 * w1[:, 1:]\n", + " grad1[:, 1:] += self.l1 * np.sign(w1[:, 1:])\n", + " grad2[:, 1:] += self.l2 * w2[:, 1:]\n", + " grad2[:, 1:] += self.l1 * np.sign(w2[:, 1:])\n", "\n", " return grad1, grad2\n", "\n", @@ -876,11 +892,87 @@ " return self" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n", + "**Note**\n", + "\n", + "In the fit method of the MLP example above,\n", + "\n", + "```python\n", + "\n", + "for idx in mini:\n", + "...\n", + " # compute gradient via backpropagation\n", + " grad1, grad2 = self._get_gradient(a1=a1, a2=a2,\n", + " a3=a3, z2=z2,\n", + " y_enc=y_enc[:, idx],\n", + " w1=self.w1,\n", + " w2=self.w2)\n", + "\n", + " delta_w1, delta_w2 = self.eta * grad1, self.eta * grad2\n", + " self.w1 -= (delta_w1 + (self.alpha * delta_w1_prev))\n", + " self.w2 -= (delta_w2 + (self.alpha * delta_w2_prev))\n", + " delta_w1_prev, delta_w2_prev = delta_w1, delta_w2\n", + "```\n", + "\n", + "`delta_w1_prev` (same applies to `delta_w2_prev`) is a memory view on `delta_w1` via \n", + "\n", + "```python\n", + "delta_w1_prev = delta_w1\n", + "```\n", + "on the last line. This could be problematic, since updating `delta_w1 = self.eta * grad1` would change `delta_w1_prev` as well when we iterate over the for loop. Note that this is not the case here, because we assign a new array to `delta_w1` in each iteration -- the gradient array times the learning rate:\n", + "\n", + "```python\n", + "delta_w1 = self.eta * grad1\n", + "```\n", + "\n", + "The assignment shown above leaves the `delta_w1_prev` pointing to the \"old\" `delta_w1` array. To illustrates this with a simple snippet, consider the following example:\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a & b True\n", + "a & b False\n" + ] + } + ], + "source": [ + "import numpy as np\n", + "\n", + "a = np.arange(5)\n", + "b = a\n", + "print('a & b', np.may_share_memory(a, b))\n", + "\n", + "\n", + "a = np.arange(5)\n", + "print('a & b', np.may_share_memory(a, b))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "(End of note.)\n", + "\n", + "---" + ] + }, { "cell_type": "code", "execution_count": 15, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -901,9 +993,7 @@ { "cell_type": "code", "execution_count": 16, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stderr", @@ -930,9 +1020,7 @@ { "cell_type": "code", "execution_count": 17, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -961,7 +1049,7 @@ "cell_type": "code", "execution_count": 18, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -973,9 +1061,7 @@ { "cell_type": "code", "execution_count": 19, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1001,9 +1087,7 @@ { "cell_type": "code", "execution_count": 20, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1028,9 +1112,7 @@ { "cell_type": "code", "execution_count": 21, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1055,9 +1137,7 @@ { "cell_type": "code", "execution_count": 22, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1092,9 +1172,7 @@ { "cell_type": "code", "execution_count": 23, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1160,9 +1238,7 @@ { "cell_type": "code", "execution_count": 24, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1202,9 +1278,7 @@ { "cell_type": "code", "execution_count": 25, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1229,9 +1303,7 @@ { "cell_type": "code", "execution_count": 26, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1287,9 +1359,7 @@ { "cell_type": "code", "execution_count": 27, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1314,9 +1384,7 @@ { "cell_type": "code", "execution_count": 6, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1576,8 +1644,10 @@ " grad2 = sigma3.dot(a2.T)\n", "\n", " # regularize\n", - " grad1[:, 1:] += (w1[:, 1:] * (self.l1 + self.l2))\n", - " grad2[:, 1:] += (w2[:, 1:] * (self.l1 + self.l2))\n", + " grad1[:, 1:] += self.l2 * w1[:, 1:]\n", + " grad1[:, 1:] += self.l1 * np.sign(w1[:, 1:])\n", + " grad2[:, 1:] += self.l2 * w2[:, 1:]\n", + " grad2[:, 1:] += self.l1 * np.sign(w2[:, 1:])\n", "\n", " return grad1, grad2\n", "\n", @@ -1738,7 +1808,7 @@ "cell_type": "code", "execution_count": 29, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -1759,9 +1829,7 @@ { "cell_type": "code", "execution_count": 30, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1812,9 +1880,7 @@ { "cell_type": "code", "execution_count": 31, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1868,9 +1934,7 @@ { "cell_type": "code", "execution_count": 32, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1895,9 +1959,7 @@ { "cell_type": "code", "execution_count": 33, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -1937,9 +1999,7 @@ { "cell_type": "code", "execution_count": 34, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ { "data": { @@ -2005,6 +2065,7 @@ } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { "display_name": "Python 3", "language": "python", @@ -2020,9 +2081,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.5.1" + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch12/images/12_02.png b/code/ch12/images/12_02.png index 16911b96..9169dd13 100644 Binary files a/code/ch12/images/12_02.png and b/code/ch12/images/12_02.png differ diff --git a/code/ch12/neuralnet.py b/code/ch12/neuralnet.py new file mode 100644 index 00000000..fc2b4a25 --- /dev/null +++ b/code/ch12/neuralnet.py @@ -0,0 +1,331 @@ +# Python Machine Learning by Sebastian Raschka, Packt Publishing Ltd. 2015 +# Code Repository: https://github.com/rasbt/python-machine-learning-book +# Code License: MIT License + +import numpy as np +from scipy.special import expit +import sys + + +class NeuralNetMLP(object): + """ Feedforward neural network / Multi-layer perceptron classifier. + + Parameters + ------------ + n_output : int + Number of output units, should be equal to the + number of unique class labels. + n_features : int + Number of features (dimensions) in the target dataset. + Should be equal to the number of columns in the X array. + n_hidden : int (default: 30) + Number of hidden units. + l1 : float (default: 0.0) + Lambda value for L1-regularization. + No regularization if l1=0.0 (default) + l2 : float (default: 0.0) + Lambda value for L2-regularization. + No regularization if l2=0.0 (default) + epochs : int (default: 500) + Number of passes over the training set. + eta : float (default: 0.001) + Learning rate. + alpha : float (default: 0.0) + Momentum constant. Factor multiplied with the + gradient of the previous epoch t-1 to improve + learning speed + w(t) := w(t) - (grad(t) + alpha*grad(t-1)) + decrease_const : float (default: 0.0) + Decrease constant. Shrinks the learning rate + after each epoch via eta / (1 + epoch*decrease_const) + shuffle : bool (default: True) + Shuffles training data every epoch if True to prevent circles. + minibatches : int (default: 1) + Divides training data into k minibatches for efficiency. + Normal gradient descent learning if k=1 (default). + random_state : int (default: None) + Set random state for shuffling and initializing the weights. + + Attributes + ----------- + cost_ : list + Sum of squared errors after each epoch. + + """ + def __init__(self, n_output, n_features, n_hidden=30, + l1=0.0, l2=0.0, epochs=500, eta=0.001, + alpha=0.0, decrease_const=0.0, shuffle=True, + minibatches=1, random_state=None): + + np.random.seed(random_state) + self.n_output = n_output + self.n_features = n_features + self.n_hidden = n_hidden + self.w1, self.w2 = self._initialize_weights() + self.l1 = l1 + self.l2 = l2 + self.epochs = epochs + self.eta = eta + self.alpha = alpha + self.decrease_const = decrease_const + self.shuffle = shuffle + self.minibatches = minibatches + + def _encode_labels(self, y, k): + """Encode labels into one-hot representation + + Parameters + ------------ + y : array, shape = [n_samples] + Target values. + + Returns + ----------- + onehot : array, shape = (n_labels, n_samples) + + """ + onehot = np.zeros((k, y.shape[0])) + for idx, val in enumerate(y): + onehot[val, idx] = 1.0 + return onehot + + def _initialize_weights(self): + """Initialize weights with small random numbers.""" + w1 = np.random.uniform(-1.0, 1.0, + size=self.n_hidden*(self.n_features + 1)) + w1 = w1.reshape(self.n_hidden, self.n_features + 1) + w2 = np.random.uniform(-1.0, 1.0, + size=self.n_output*(self.n_hidden + 1)) + w2 = w2.reshape(self.n_output, self.n_hidden + 1) + return w1, w2 + + def _sigmoid(self, z): + """Compute logistic function (sigmoid) + + Uses scipy.special.expit to avoid overflow + error for very small input values z. + + """ + # return 1.0 / (1.0 + np.exp(-z)) + return expit(z) + + def _sigmoid_gradient(self, z): + """Compute gradient of the logistic function""" + sg = self._sigmoid(z) + return sg * (1.0 - sg) + + def _add_bias_unit(self, X, how='column'): + """Add bias unit (column or row of 1s) to array at index 0""" + if how == 'column': + X_new = np.ones((X.shape[0], X.shape[1] + 1)) + X_new[:, 1:] = X + elif how == 'row': + X_new = np.ones((X.shape[0] + 1, X.shape[1])) + X_new[1:, :] = X + else: + raise AttributeError('`how` must be `column` or `row`') + return X_new + + def _feedforward(self, X, w1, w2): + """Compute feedforward step + + Parameters + ----------- + X : array, shape = [n_samples, n_features] + Input layer with original features. + w1 : array, shape = [n_hidden_units, n_features] + Weight matrix for input layer -> hidden layer. + w2 : array, shape = [n_output_units, n_hidden_units] + Weight matrix for hidden layer -> output layer. + + Returns + ---------- + a1 : array, shape = [n_samples, n_features+1] + Input values with bias unit. + z2 : array, shape = [n_hidden, n_samples] + Net input of hidden layer. + a2 : array, shape = [n_hidden+1, n_samples] + Activation of hidden layer. + z3 : array, shape = [n_output_units, n_samples] + Net input of output layer. + a3 : array, shape = [n_output_units, n_samples] + Activation of output layer. + + """ + a1 = self._add_bias_unit(X, how='column') + z2 = w1.dot(a1.T) + a2 = self._sigmoid(z2) + a2 = self._add_bias_unit(a2, how='row') + z3 = w2.dot(a2) + a3 = self._sigmoid(z3) + return a1, z2, a2, z3, a3 + + def _L2_reg(self, lambda_, w1, w2): + """Compute L2-regularization cost""" + return (lambda_/2.0) * (np.sum(w1[:, 1:] ** 2) + + np.sum(w2[:, 1:] ** 2)) + + def _L1_reg(self, lambda_, w1, w2): + """Compute L1-regularization cost""" + return (lambda_/2.0) * (np.abs(w1[:, 1:]).sum() + + np.abs(w2[:, 1:]).sum()) + + def _get_cost(self, y_enc, output, w1, w2): + """Compute cost function. + + Parameters + ---------- + y_enc : array, shape = (n_labels, n_samples) + one-hot encoded class labels. + output : array, shape = [n_output_units, n_samples] + Activation of the output layer (feedforward) + w1 : array, shape = [n_hidden_units, n_features] + Weight matrix for input layer -> hidden layer. + w2 : array, shape = [n_output_units, n_hidden_units] + Weight matrix for hidden layer -> output layer. + + Returns + --------- + cost : float + Regularized cost. + + """ + term1 = -y_enc * (np.log(output)) + term2 = (1.0 - y_enc) * np.log(1.0 - output) + cost = np.sum(term1 - term2) + L1_term = self._L1_reg(self.l1, w1, w2) + L2_term = self._L2_reg(self.l2, w1, w2) + cost = cost + L1_term + L2_term + return cost + + def _get_gradient(self, a1, a2, a3, z2, y_enc, w1, w2): + """ Compute gradient step using backpropagation. + + Parameters + ------------ + a1 : array, shape = [n_samples, n_features+1] + Input values with bias unit. + a2 : array, shape = [n_hidden+1, n_samples] + Activation of hidden layer. + a3 : array, shape = [n_output_units, n_samples] + Activation of output layer. + z2 : array, shape = [n_hidden, n_samples] + Net input of hidden layer. + y_enc : array, shape = (n_labels, n_samples) + one-hot encoded class labels. + w1 : array, shape = [n_hidden_units, n_features] + Weight matrix for input layer -> hidden layer. + w2 : array, shape = [n_output_units, n_hidden_units] + Weight matrix for hidden layer -> output layer. + + Returns + --------- + grad1 : array, shape = [n_hidden_units, n_features] + Gradient of the weight matrix w1. + grad2 : array, shape = [n_output_units, n_hidden_units] + Gradient of the weight matrix w2. + + """ + # backpropagation + sigma3 = a3 - y_enc + z2 = self._add_bias_unit(z2, how='row') + sigma2 = w2.T.dot(sigma3) * self._sigmoid_gradient(z2) + sigma2 = sigma2[1:, :] + grad1 = sigma2.dot(a1) + grad2 = sigma3.dot(a2.T) + + # regularize + grad1[:, 1:] += self.l2 * w1[:, 1:] + grad1[:, 1:] += self.l1 * np.sign(w1[:, 1:]) + grad2[:, 1:] += self.l2 * w2[:, 1:] + grad2[:, 1:] += self.l1 * np.sign(w2[:, 1:]) + + return grad1, grad2 + + def predict(self, X): + """Predict class labels + + Parameters + ----------- + X : array, shape = [n_samples, n_features] + Input layer with original features. + + Returns: + ---------- + y_pred : array, shape = [n_samples] + Predicted class labels. + + """ + if len(X.shape) != 2: + raise AttributeError('X must be a [n_samples, n_features] array.\n' + 'Use X[:,None] for 1-feature classification,' + '\nor X[[i]] for 1-sample classification') + + a1, z2, a2, z3, a3 = self._feedforward(X, self.w1, self.w2) + y_pred = np.argmax(z3, axis=0) + return y_pred + + def fit(self, X, y, print_progress=False): + """ Learn weights from training data. + + Parameters + ----------- + X : array, shape = [n_samples, n_features] + Input layer with original features. + y : array, shape = [n_samples] + Target class labels. + print_progress : bool (default: False) + Prints progress as the number of epochs + to stderr. + + Returns: + ---------- + self + + """ + self.cost_ = [] + X_data, y_data = X.copy(), y.copy() + y_enc = self._encode_labels(y, self.n_output) + + delta_w1_prev = np.zeros(self.w1.shape) + delta_w2_prev = np.zeros(self.w2.shape) + + for i in range(self.epochs): + + # adaptive learning rate + self.eta /= (1 + self.decrease_const*i) + + if print_progress: + sys.stderr.write('\rEpoch: %d/%d' % (i+1, self.epochs)) + sys.stderr.flush() + + if self.shuffle: + idx = np.random.permutation(y_data.shape[0]) + X_data, y_enc = X_data[idx], y_enc[:, idx] + + mini = np.array_split(range(y_data.shape[0]), self.minibatches) + for idx in mini: + + # feedforward + a1, z2, a2, z3, a3 = self._feedforward(X_data[idx], + self.w1, + self.w2) + cost = self._get_cost(y_enc=y_enc[:, idx], + output=a3, + w1=self.w1, + w2=self.w2) + self.cost_.append(cost) + + # compute gradient via backpropagation + grad1, grad2 = self._get_gradient(a1=a1, a2=a2, + a3=a3, z2=z2, + y_enc=y_enc[:, idx], + w1=self.w1, + w2=self.w2) + + delta_w1, delta_w2 = self.eta * grad1, self.eta * grad2 + self.w1 -= (delta_w1 + (self.alpha * delta_w1_prev)) + self.w2 -= (delta_w2 + (self.alpha * delta_w2_prev)) + delta_w1_prev, delta_w2_prev = delta_w1, delta_w2 + + return self \ No newline at end of file diff --git a/code/ch12/optional-streamlined-neuralnet.py b/code/ch12/optional-streamlined-neuralnet.py new file mode 100644 index 00000000..4af365ca --- /dev/null +++ b/code/ch12/optional-streamlined-neuralnet.py @@ -0,0 +1,256 @@ +# Python Machine Learning by Sebastian Raschka, Packt Publishing Ltd. 2015 +# Code Repository: https://github.com/rasbt/python-machine-learning-book +# Code License: MIT License + +import numpy as np +import sys + + +class NeuralNetMLP(object): + """ Feedforward neural network / Multi-layer perceptron classifier. + + Parameters + ------------ + n_hidden : int (default: 30) + Number of hidden units. + l2 : float (default: 0.) + Lambda value for L2-regularization. + No regularization if l2=0. (default) + epochs : int (default: 100) + Number of passes over the training set. + eta : float (default: 0.001) + Learning rate. + shuffle : bool (default: True) + Shuffles training data every epoch if True to prevent circles. + minibatche_size : int (default: 1) + Number of training samples per minibatch. + seed : int (default: None) + Random seed for initializing weights and shuffling. + + Attributes + ----------- + eval_ : dict + Dictionary collecting the cost, training accuracy, + and validation accuracy for each epoch during training. + + """ + def __init__(self, n_hidden=30, + l2=0., epochs=100, eta=0.001, + shuffle=True, minibatch_size=1, seed=None): + + self.random = np.random.RandomState(seed) + self.n_hidden = n_hidden + self.l2 = l2 + self.epochs = epochs + self.eta = eta + self.shuffle = shuffle + self.minibatch_size = minibatch_size + + def _onehot(self, y, n_classes): + """Encode labels into one-hot representation + + Parameters + ------------ + y : array, shape = [n_samples] + Target values. + + Returns + ----------- + onehot : array, shape = (n_samples, n_labels) + + """ + onehot = np.zeros((n_classes, y.shape[0].astype(int))) + for idx, val in enumerate(y): + onehot[val, idx] = 1. + return onehot.T + + def _sigmoid(self, z): + """Compute logistic function (sigmoid)""" + return 1. / (1. + np.exp(-np.clip(z, -250, 250))) + + def _forward(self, X): + """Compute forward propagation step""" + + # step 1: net input of hidden layer + # [n_samples, n_features] dot [n_features, n_hidden] + # -> [n_samples, n_hidden] + z_h = np.dot(X, self.w_h) + self.b_h + + # step 2: activation of hidden layer + a_h = self._sigmoid(z_h) + + # step 3: net input of output layer + # [n_samples, n_hidden] dot [n_hidden, n_classlabels] + # -> [n_samples, n_classlabels] + + z_out = np.dot(a_h, self.w_out) + self.b_out + + # step 4: activation output layer + a_out = self._sigmoid(z_out) + + return z_h, a_h, z_out, a_out + + def _compute_cost(self, y_enc, output): + """Compute cost function. + + Parameters + ---------- + y_enc : array, shape = (n_samples, n_labels) + one-hot encoded class labels. + output : array, shape = [n_samples, n_output_units] + Activation of the output layer (forward propagation) + + Returns + --------- + cost : float + Regularized cost + + """ + L2_term = (self.l2 * + (np.sum(self.w_h ** 2.) + + np.sum(self.w_out ** 2.))) + + term1 = -y_enc * (np.log(output)) + term2 = (1. - y_enc) * np.log(1. - output) + cost = np.sum(term1 - term2) + L2_term + return cost + + def predict(self, X): + """Predict class labels + + Parameters + ----------- + X : array, shape = [n_samples, n_features] + Input layer with original features. + + Returns: + ---------- + y_pred : array, shape = [n_samples] + Predicted class labels. + + """ + z_h, a_h, z_out, a_out = self._forward(X) + y_pred = np.argmax(z_out, axis=1) + return y_pred + + def fit(self, X_train, y_train, X_valid, y_valid): + """ Learn weights from training data. + + Parameters + ----------- + X_train : array, shape = [n_samples, n_features] + Input layer with original features. + y_train : array, shape = [n_samples] + Target class labels. + X_valid : array, shape = [n_samples, n_features] + Sample features for validation during training + y_valid : array, shape = [n_samples] + Sample labels for validation during training + + Returns: + ---------- + self + + """ + n_output = np.unique(y_train).shape[0] # number of class labels + n_features = X_train.shape[1] + + ######################## + # Weight initialization + ######################## + + # weights for input -> hidden + self.b_h = np.zeros(self.n_hidden) + self.w_h = self.random.normal(loc=0.0, scale=0.1, + size=(n_features, self.n_hidden)) + + # weights for hidden -> output + self.b_out = np.zeros(n_output) + self.w_out = self.random.normal(loc=0.0, scale=0.1, + size=(self.n_hidden, n_output)) + + epoch_strlen = len(str(self.epochs)) # for progress formatting + self.eval_ = {'cost': [], 'train_acc': [], 'valid_acc': []} + + y_train_enc = self._onehot(y_train, n_output) + + # iterate over training epochs + for i in range(self.epochs): + + # iterate over minibatches + indices = np.arange(X_train.shape[0]) + + if self.shuffle: + self.random.shuffle(indices) + + for start_idx in range(0, indices.shape[0] - self.minibatch_size + + 1, self.minibatch_size): + batch_idx = indices[start_idx:start_idx + self.minibatch_size] + + # forward propagation + z_h, a_h, z_out, a_out = self._forward(X_train[batch_idx]) + + ################## + # Backpropagation + ################## + + # [n_samples, n_classlabels] + sigma_out = a_out - y_train_enc[batch_idx] + + # [n_samples, n_hidden] + sigmoid_derivative_h = a_h * (1. - a_h) + + # [n_samples, n_classlabels] dot [n_classlabels, n_hidden] + # -> [n_samples, n_hidden] + sigma_h = (np.dot(sigma_out, self.w_out.T) * + sigmoid_derivative_h) + + # [n_features, n_samples] dot [n_samples, n_hidden] + # -> [n_features, n_hidden] + grad_w_h = np.dot(X_train[batch_idx].T, sigma_h) + grad_b_h = np.sum(sigma_h, axis=0) + + # [n_hidden, n_samples] dot [n_samples, n_classlabels] + # -> [n_hidden, n_classlabels] + grad_w_out = np.dot(a_h.T, sigma_out) + grad_b_out = np.sum(sigma_out, axis=0) + + # Regularization and weight updates + delta_w_h = (grad_w_h + self.l2*self.w_h) + delta_b_h = grad_b_h # bias is not regularized + self.w_h -= self.eta * delta_w_h + self.b_h -= self.eta * delta_b_h + + delta_w_out = (grad_w_out + self.l2*self.w_out) + delta_b_out = grad_b_out # bias is not regularized + self.w_out -= self.eta * delta_w_out + self.b_out -= self.eta * delta_b_out + + ############# + # Evaluation + ############# + + # Evaluation after each epoch during training + z_h, a_h, z_out, a_out = self._forward(X_train) + cost = self._compute_cost(y_enc=y_train_enc, + output=a_out) + + y_train_pred = self.predict(X_train) + y_valid_pred = self.predict(X_valid) + + train_acc = ((np.sum(y_train == y_train_pred)).astype(np.float) / + X_train.shape[0]) + valid_acc = ((np.sum(y_valid == y_valid_pred)).astype(np.float) / + X_valid.shape[0]) + + sys.stderr.write('\r%0*d/%d | Cost: %.2f ' + '| Train/Valid Acc.: %.2f%%/%.2f%% ' % + (epoch_strlen, i+1, self.epochs, cost, + train_acc*100, valid_acc*100)) + sys.stderr.flush() + + self.eval_['cost'].append(cost) + self.eval_['train_acc'].append(train_acc) + self.eval_['valid_acc'].append(valid_acc) + + return self \ No newline at end of file diff --git a/code/ch13/ch13.ipynb b/code/ch13/ch13.ipynb index 76089816..93492a53 100644 --- a/code/ch13/ch13.ipynb +++ b/code/ch13/ch13.ipynb @@ -35,24 +35,29 @@ { "cell_type": "code", "execution_count": 1, - "metadata": { - "collapsed": false - }, + "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Using Theano backend.\n" + ] + }, { "name": "stdout", "output_type": "stream", "text": [ "Sebastian Raschka \n", - "Last updated: 08/27/2015 \n", + "last updated: 2017-07-04 \n", "\n", - "CPython 3.4.3\n", - "IPython 4.0.0\n", + "CPython 3.6.1\n", + "IPython 6.0.0\n", "\n", - "numpy 1.9.2\n", - "matplotlib 1.4.3\n", - "theano 0.7.0\n", - "keras 0.1.2\n" + "numpy 1.13.0\n", + "matplotlib 2.0.2\n", + "theano 0.9.0\n", + "keras 2.0.5\n" ] } ], @@ -105,7 +110,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": { "collapsed": true }, @@ -116,7 +121,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "collapsed": true }, @@ -145,10 +150,8 @@ }, { "cell_type": "code", - "execution_count": 3, - "metadata": { - "collapsed": false - }, + "execution_count": 4, + "metadata": {}, "outputs": [ { "data": { @@ -157,7 +160,7 @@ "" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": { "image/png": { "width": 500 @@ -208,9 +211,9 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -220,18 +223,16 @@ }, { "cell_type": "code", - "execution_count": 4, - "metadata": { - "collapsed": false - }, + "execution_count": 6, + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array(2.5)" + "array(2.5, dtype=float32)" ] }, - "execution_count": 4, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -276,16 +277,14 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "collapsed": false - }, + "execution_count": 7, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "float64\n" + "float32\n" ] } ], @@ -295,7 +294,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": { "collapsed": true }, @@ -328,10 +327,8 @@ }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "collapsed": false - }, + "execution_count": 9, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -390,10 +387,8 @@ }, { "cell_type": "code", - "execution_count": 13, - "metadata": { - "collapsed": false - }, + "execution_count": 10, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -435,10 +430,8 @@ }, { "cell_type": "code", - "execution_count": 9, - "metadata": { - "collapsed": false - }, + "execution_count": 11, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -480,10 +473,8 @@ }, { "cell_type": "code", - "execution_count": 10, - "metadata": { - "collapsed": false - }, + "execution_count": 12, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -542,7 +533,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 13, "metadata": { "collapsed": true }, @@ -567,9 +558,9 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 14, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -620,16 +611,14 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": { - "collapsed": false - }, + "execution_count": 15, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -660,16 +649,14 @@ }, { "cell_type": "code", - "execution_count": 23, - "metadata": { - "collapsed": false - }, + "execution_count": 16, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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fMmUKFRUVLF68WIc0EhHPUUglgY6ODqqrq3nvvfci6suXL6esrIysrCxHnYmI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\n", 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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -746,10 +733,8 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": { - "collapsed": false - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -788,10 +773,8 @@ }, { "cell_type": "code", - "execution_count": 30, - "metadata": { - "collapsed": false - }, + "execution_count": 18, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -807,7 +790,7 @@ "source": [ "# W : array, shape = [n_output_units, n_hidden_units+1]\n", "# Weight matrix for hidden layer -> output layer.\n", - "# note that first column (A[:][0] = 1) are the bias units\n", + "# note that first column (W[:][0]) contains the bias units\n", "W = np.array([[1.1, 1.2, 1.3, 0.5],\n", " [0.1, 0.2, 0.4, 0.1],\n", " [0.2, 0.5, 2.1, 1.9]])\n", @@ -831,10 +814,8 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": { - "collapsed": false - }, + "execution_count": 19, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -879,7 +860,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 20, "metadata": { "collapsed": true }, @@ -895,10 +876,8 @@ }, { "cell_type": "code", - "execution_count": 33, - "metadata": { - "collapsed": false - }, + "execution_count": 21, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -918,10 +897,8 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": { - "collapsed": false - }, + "execution_count": 22, + "metadata": {}, "outputs": [ { "data": { @@ -929,7 +906,7 @@ "1.0" ] }, - "execution_count": 34, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -940,10 +917,8 @@ }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 23, + "metadata": {}, "outputs": [ { "data": { @@ -951,7 +926,7 @@ "array([2])" ] }, - "execution_count": 35, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -961,6 +936,39 @@ "y_class" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "***Note*** \n", + "Below is an additional figure to illustrate the difference between logistic regression and softmax:" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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JSUhOTkZ6ejp69OiBnj17Iisrq0Fxguk2uKETERABERCBMAFpWCPnUVBdR05dq6QiIAIi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\n3aP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Zy7Tcdsp29TkeGdcSxMF0+OJRmupvDjzEv+kweZ24++E4TAB3wORnImw7ZjAhn6Ty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lXynCyVTcu3qb5lkY4J1VJRXq28AsQAc2TLrn1ScqhKsrqEmWrYNyjW9qxftECk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\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TpRISLC62HuXl5di6dSveffddrFixwtw/ElV0X6mNao/6kFJhIckgpisoyI0bN84IJLKs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UrrL9LQo99UZ1u/2rttMoPC0T+pfOicAfVbh4G1G/Zoss2dMCNv\nQI89cL9e2GgHv+JdNneyhxLWvB1M7DwyTr+fhy8xb/a2F/5Z2AJuL1OyPVQIVrBpDjKVlZGlGfYy\nta9H7V0d6u7N01B7izqbDylRUKPsU6prsMMx/8cb0/3hocHevXu1bt06veUtb9FVV12lvLy84Pjh\nUECnVpkBm3Laem/kS7MmSBOKbB/u5iHMOVi8rpdddpn1KInrU5/6lG5+29vU2Nio0tLSkR4m56AS\nHAIBBBBAAAEEEDgHAqP/yj0Hh+MQCCCAAAIIIIAAAggggMAZCoy0rwdj9AylWRBwWA1rd+nnD2Wp\nIKtffc312tJSofSZi/XFlXNUUZor9TfbLfp+l75NjmyhQNGky1TauEszWw9qy0trlWhK08GNG7Rr\n72Ep11qkrak+0d2s1j0vaEP7XvVZQlGZ1aLd9T2KX/FhVZXnqTDbGvh9CVr1vcE/UxXVVaq9drnW\nbF6jp1P2q2dHTJsO9ag5Vq78NAsarNvDkPcaGLKy1WVwyBu9h3fjzz4J8oBN4By9bQ3ig92DVvXh\nlZLKVU5+qRZcadNB79uotY9nK3ZgniZld6hgaIc2Nu9WnzVuV2a1nriuI4c6V08eGrh5fX29tm7d\nqoULFwY9DQoLC9/EEEWja+teFkbYfNg9By00civDCglHrzlW5dzcXJWXl+s973mPWltbtHnzZl1+\n+eXKyLAgypY3F4SMVS3ZLwIIIIAAAgggcGYCBAdn5sfWCCCAAAIIIIAAAgggcN4E0myM/1y74Xy/\n1eAeferj/xbVZMmtf6T3Llul971joSYXD6lzr807kO5DBSWVkZ6pKQtv1ED7o5q26Y/0x38QbWaF\nSnvcprhNuJvsb1Hzqw/p37/2P3pix8g6Mz+i295zq+ZPL1d1od357ne6B8GBhQGxbE2ZPU8LWt+m\nT7zvC3piZJNf+cQHFJ9Yp0kNKbI5lW29lGAOBJ8HIS1uPRCC7Yffj9kuU1JalGbHT/EP7I3Ugbjd\nY2+vbZyjpPWGyCur1sIPf0zbHvi+/u2Ob0mL/06ff3tSV01Zq3/94nf1lJ1rsJy0riOfj/FT2Ntg\nwIZS2rFjh1avXq2VK1dqypQpZ9S47lw+Y0TIFpyGfw+mEzwFbxz9Zywa8j08uOaaa7TfJtV+9NFH\nNWPGDOXn5wffkR95LI559IwoIYAAAggggAACYy8Qsz/mzuXNGWN/RhwBAQQQQAABBBBAAAEELgmB\n5KDNXdDfqcNN7Wpps6GIvLHfft54o216Zr6yrXG3sDBP6Xa71JAN69N8wFrUs4uUZnfs56f1q7ej\nXY2Hj6izz+7yH4opI8t6LyiutLQsTZhcaaVeJTqbdaSlU909CesNkGKTGecpO79A5aX5yvRG/+Ok\nh/q71N3ZrvrDjertt34CsTQVFOXYeulK9KapfEKhcrKk3pZ6dQ1mqS8lXxVFGVZHG8DIJkxuPXhA\nfTY3QlrpFOVk+lZ92r+7WRm5OSqsLLWhmOxcbGimnrZGNVq9OnoGFM+vUH5WTHlpvfaeDV10inU9\nrupn/aX3NBgcHAzmAPje976nO+64Q3/+538e9Dqoqqp608dL2uzWsViP1t5/h+770u/pv5+Tpr73\nN/SRT39ZN80v10TrWHKuls7OTq1fvz4IDXz4pa985Suqq6sLggMPeAgOztU3wXEQQAABBBBAYKwE\n6HEwVrLsFwEEEEAAAQQQQAABBMZUIJaarrSsYlVN8sfrHyolI1vlU2ePWilNuSXZ9rAeBnYrlbVJ\n+839xy25Nj9CrvJKj3v7dV6mpOcotzhHM4p9uKOTLzmlNfJpmEcvMQsZiiZOGf2WldM1ZcbwXADh\nBynpw70O8srCd44+WyYyLpbRvQ28kb29vV0NDQ3ywKC4uPis1XHIhnwa6GvX4X2tFvNYiNTaa8HJ\nYBAAFRQVq7yyTGUVRcqwwCX1+JTnDGqRnp6u2tpaec8DDw66u7uDCaB97oM3M+HzGVSBTRFAAAEE\nEEAAgTEVIDgYU152jgACCCCAAAIIIIAAAmMrcOLhacJjjr7zO+psbT0SvA05eu0rW8PyMX2xg3VO\nvu/R+w2PNfx88m2GPx+eEPnosYdfh/t47ftH9zf6mEfXC7c8+fPo7U6+1tn7xOsW1s97TzQ1Namj\noyOYA8AnEc7Kygo+P6N6WdjjQc9Ab4c6j+zSi5tfUPPO5/RfD23Ryxu32clcrmve/Vb96q/drOuu\nW6YJeTFl++zYZ2nxgGDixIkWHOQE8zf4+fX29gaTJofnfkbnd5bqyW4QQAABBBBAAIHTFSA4OF05\ntkMAAQQQQAABBBBAAIFxIHBsw/vrVej4htzjX79221Pf99FtT22bkx37te+feH+vXe9oDcZTqaen\nRwcPHpTPczB//nwbBurs/AT1HiIZ1RO1a+sr+vF3/13p3YfU3XxAO3ccsNPPUX55sw5sfUD339On\nlzc06GO/eqXm15UpbWQoqzM1Cv1zcnI1efLkIBxpbGxUdna2UlNf03XlTA/H9ggggAACCCCAwDkX\nODt/tZ3zanNABBBAAAEEEEAAAQQQQACB8S7Q398fNKr7XfgVFRVntVE9lhpX/c5tqt9lPQwyq1VT\nW6p5CysUG+pVb1enGnY/rx9vHTCiI1px9VRVTylTsbXpn41mfT8fDw8yMzPlQxb5UExtbW3yeR3C\nz8b7d0P9EEAAAQQQQACB1xMgOHg9HT5DAAEEEEAAAQQQQAABBBB40wLeeO6N6B4ctLW3BdsXFBSc\n5fH/beghmxDbZq3Wuz7yMb3l2uv1zivrpNZN2rb2Qf31J+9TT1mbWo7cofVb3qNJk+u0vCbDwouz\nO2RRQWGBurpsUmyb58DPmwUBBBBAAAEEELgYBAgOLoZvkXNAAAEEEEAAAQQQQAABBMaRgDeg+2Nw\ncFC9Pb3B3fk+jE84xM8ZV9Xa/pODnZoy63LNXXaTPvDum7XksjmaXm3hRH+OciwcePcH1ujJF/fp\noSPSzlebtf9why6fnK64dTnw5v2zER/4JMkeiPhcDj7HQdjjwM/9rJ3rGWOxAwQQQAABBBBA4M0L\n2O0ZLAgggAACCCCAAAIIIIAAAgicHYHRd917Q7qHBykpKWdpfoOR5n57GmxuVHlVnZa99YNafvlC\nzfbQwI6Xkl6s4ur5Wrp4ombWZgQndai5W82t3iPguHMcCTiCoOO4j07lpZ9XRnpGcI5+nsmhoxND\nn8r2rIMAAggggAACCIxXAYKD8frNUC8EEEAAAQQQQAABBBBA4AIW8NDAl3g8HkyOfHaG8hlu+bfp\nBZRol3JzM1U9sUhZmfHgWOFd/ml2zKpps1RhExf7kpVu9Rjd3952E+zJduTbBI9gzTf3TyKRCOY2\niNukzz7x85DN2hyEEK9JKN7cflkbAQQQQAABBBA43wKj/3Q633Xh+AgggAACCCCAAAIIIIAAAheJ\ngDeg+x35OTk5wRA+PoFwGCacjVP0hv9Um+MgIyPNjnPswEMpsRTl5hcoy47ti09r4GHD0WVIsWS/\n2psa1XikUYNZlcrOK9CEoszX7OvoNq8t+RBFzc3NSs/ICCZKfu0avIMAAggggAACCFyYAvQ4uDC/\nN2qNAAIIIIAAAggggAACCIxPgZEGeg8O/C78vLy8IDBoamo6q8GBH2bQhgbqGxiyO/1PQGHhgfxx\ngiU5mNBA12HtWP+E7vv3L+qeh5/Xmq0tGrCJlt/M4sHBvn37gnDkrM7h8GYqwboIIIAAAggggMAY\nCNDjYAxQ2SUCCCCAAAIIIIAAAgggcMkKjDTie3CQYXfiV1RUBBSbN28O5gI4uy4+zFBKMNTQ6P0O\nWgDQuH+/Whsagrd7+pNKDAxXrK9ll3ZuXqc7739Su3fu1qE9L6ok7V2qqB2IAghf85gOCqN37p+N\ndF/w4Ze2b9+u/Px8FRYWRu8ftzovEUAAAQQQQACBC06A4OCC+8qoMAIIIIAAAggggAACCCAwfgXC\nRnV/9vkNvFHdn3ft2qWurq5gDoAzrb1PIRAvljpaO7Rn2z41TchUaXae4qne4D+o/u4W7d6yV/V7\nGoNDZdgEBz4PgS+97Q06vPsF3fnAM9q5ca/mTm7SQEefuvus50Kwxhv/40Mu9fb2yoMDX7JzspWV\nlRUFB6HBG++JNRBAAAEEEEAAgfEpQHAwPr8XaoUAAggggAACCCCAAAIIXLAC3nDuDx+qyIfw8eGK\npkyZoldffVVFRUUqLS09s3OzFv54UZU2vbJF6z52h0q/9+tKvX6+ZpbZHAV9B9W673k9+sA2Pb+j\nLThOVUWOKkpzlGpzIbS3dGmoP67PfOHrSmncoOzD/6KnlGtDHo10lTiFmvkQRd7TwOdtWL58ubKz\nsm2+BUstbCE0OAVAVkEAAQQQQACBcS9AcDDuvyIqiAACCCCAAAIIIIAAAghceALegO6N6d7boKCg\nQNXV1dqyZUsQGpxJcODN+4P2GFKqupvrrfSUfnZfXAf31mnRrCoNNu7R3pef09pd9WrMmyi1z9f8\nadWaPiUvCA7yK6aq7vJsVZfMVeeuDjX3xJTVnWLzJZy6sfc22LBhg1pbWzVnzhylp6cHE0H7ZNBh\naHLqe2NNBBBAAAEEEEBg/AkQHIy/74QaIYAAAggggAACCCCAAAIXvIA3oHtDuj88OJgwYYI2btyo\nqVOnat68eafZwG4zD3hvhgwp0+7yLy/tVtvhDfrp3f6Q3nLTMjVu2KXNBxs1ZaqU7F1ujldo2pQq\nTS6OK2ZjHBVMqLVHjb0f08GmdB1J9AXzGbzenAbhl+HzNvh5+RBFL730knp6ejR58uRgLgcCg1CJ\nZwQQQAABBBC4GARSLoaT4BwQQAABBBBAAAEEEEAAAQTGj0DYiO6hgfc4qKmpCe7Mf+ihh4LhigYG\nBk6zstZwn+zXUJP00sYtashcoN/97O/pprqyYH9PPvxcEBr4i727lmrVr/2KfvDkb2rRjEpl2XsW\nOQTr+RwJvtjelLQg4NQHKbLeDoODQU+Dxx57LDi3pUuXBkMxee+KsMfB8N75FwEEEEAAAQQQuHAF\n6HFw4X531BwBBBBAAAEEEEAAAQQQGJcCo3sb+DwHxcXFqqqqCu7Mr6+vD+YH8DAhJyfnlOtv7fu2\nxFVaPUsrPvF7+j+vTlBBRYWWX1GleYUVunr3PtVbAjAwmFR6Vq4yi2bryrcs1RVLqlVqPRSCzYdz\ng+iYHhiEj+jNNyjs27dP27ZtU0dHR3Be3pMiIyMj6l3h586CAAIIIIAAAghc6AIEBxf6N0j9EUAA\nAQQQQAABBBBAAIFxKOB33/td+B4c5Obmqry8XCtWrNChQ4f0wAMP6L3vfa/q6uoUDv/zxqfgHebT\nVXPZKk2ed7VW2QTHfoz0jBQll61Qor9PbZ09NleBHzNDefm5So+n2Trer+D1GvNH9TcIuyKcoDJJ\nixj6+/v17OpntfrZ1VqyZEkQhvi5ea+K0T0OCA9OAMhbCCCAAAIIIHBBCTBU0QX1dVFZBBBAAAEE\nEEAAAQQQQGB8C4TDFHlDezhUUThB8vXXX6+srCzdeeed2rFjh9rb29/0ycRS0pUaz7XeChm2L2uw\nT7GgID1XWbnFKiurVGVFucpKi5Sdma60VJtjwXoAHN8JIGzY989SY8PrBHMnWBDhy4lihp7uHu3c\nuVPr1q7Tyy+/rKuvvlrTp08PJkb2yZE9IAn3+6ZPig0QQAABBBBAAIFxJkBwMM6+EKqDAAIIIIAA\nAggggAACCFwMAn6XfywlFjSoe3CQnZ0dTIw8ceLEYHLh9evXa9OmTcEEw0NDQ2/ulK1ngPdU8Icv\n/pRMWgiQmjZy57/NW+DvnWCvQ4MDGujv0YAds6+vVwl7DCb67dGnvt5eG+poUAmrTritH8Pr50Ms\nPf7449q/f3/Qe6K2tlalpaVBcOChgfc4IDg4AThvIYAAAggggMAFKUBwcEF+bVQaAQQQOBcCx/4g\nPxdHPFvHCBsSgueztVP2gwACCCCAAAJvSsAb0VPsbv5Uu+vfg4PMzEzl5+drypQpevvb364HH3xQ\nd999d9Ag39fXF+w7DALe8EBBLwLvSTDcN8CfRorRpsF70aujhcH+LnW3N+hQQ709GtXU3Kie9iPq\nbD2kg4cPqamjR902d/PQSCjhoUFbW5vWrVunT3ziE8F8BitXrlRhYWHQe8LnNwhDg7A+R49GCQEE\nEEAAAQQQuDAFUv/Clguz6tQaAQQQQGBsBYZ/jF+IP4D7u5rVcniv3cW4RYeae9Q5lKXMeKrS08jL\nx/aaYe8IIIAAAggcFQj+hrAG/eHeAMM3JIQ9CzxI6O7u1uHDh4OJhv3O/UmTJgUbj+3fHkk173le\nm1ffrx89slZPP/W0XnppvTa8mqojhw9o/7Z16ogVKLWgSiXZMcVTY+rs7NS9996rNWvWBHM1eGgw\ne/ZsGxapLHjtQy+lx234JOtx4EMzjW39j/pSQgABBBBAAAEExlKAyZHHUpd9I4AAAheoQHKwTwOJ\nHjW2Wif9lLgqynKC8YHPy+kkB5UcGlS/3flnlbEJEG384JNVJOnjCvTp4O6t2vLS83plX7Oyqxer\nalahCrPTlJOZGgw7cNLtT7bf6H0ftMAmRuxLBI0gqekZ5mK1Ov0dRnumgAACCCCAwMUo4MMVeWO6\nD+Xjd+YnEomgwd0b11tbW/Xss8/qG9/4RtALwXsilJSUBL0TxrLxva/jsA7veFA/vrdZW5oGNal4\nidKT+9S6c6+++cNN+nT1Mk2YmVCiWBrs7QzmNfje976nQRvC6JprrtHsObODSZFzcnKCc/IQJDVt\nODS4GL9DzgkBBBBAAAEELk0BgoNL83vnrBFAAIGTCHjDeEz9HXt0eM8z+ubdScULa/THn3yLNbzH\nFRvpsn/Mxt5obmMKHzM8gK0XjgscrOsfjmx7TEPAyHrHvOe7G7XuYKJb/V0t2teQVCyerdopJcFE\nhydqq08OdSnRuVNP/uIn+ts/+LLm/9bHVZ0zR1kN3RqoyQ+qkhyymvnGQb39rdepe7SOrRWcoI+/\n3KtD++rVm0hVQXWN8jNTlBX387WVR9Xb93x0Gf7cdze8+F2XYdmebd9HP7PXIy4Barji8evYEaOP\nfJPjz2PU7ikigAACCCBwvgT8v58eHPjd+OFwRR4e5OXladGiRcH8AD09PcHcAU1NTcFQQH4nv6/v\ni/9NcPzfCWd2LjFVzFmlG6cs1eIPJTQwMBT8N/jof5aTyisqU3ZuppL93Xr+hRd13333qbi4WNXV\n1Vq6dKkmVE4IhijyORt8UmSGKTqzb4StEUAAAQQQQGB8ChAcjM/vhVohgAAC50fAfzV7C7b1OOjv\nPKJXd0mZ5SXqHxz+OX3SH+7HtHr7Po5rCPezsfdes5xovWDVo+sm+9vU3bxFq1fbhIc5FZo4uUzx\n1+xouOLJgV71t+1TU2u/XtBt+s2Vq1Q3bZaKcvOUnTW8Vcro7gFHD3N0j8fX6Zh1rIGhr0nPPfe0\nmrrTNf+GCk2vzLHgYOR8T3SOwZ6P97DXx+w3hB+pxug6HLvi0XoeFxQcs7tRa1FEAAEEEEBgPAiE\nvQ68od3nOhgYCLoSqra2Vj70z86dO7Vjxw498sgjmjNnTvC+zyHg253tJZ6ZL3/klZx4z729PTp4\nYLc2bHxFmzdvVnt7e1An7xFRXl4ehB7B8ER2LkyKfGJD3kUAAQQQQACBC1+A4ODC/w45AwQQQODs\nC9hEhkmlKZmwDKHffrBbu3ZSAxro71ffgL0eGlCKfdjTbx/YUEbZ2VmK2/wBPvlhsKaNK5Tos3Ws\nrX5wcEC9PX2KpWUq1X5gZ2dYd35bzRu6E73dVrCxgNPtM28sj/mBBtRvx00MJK2xP109HQe0d8tD\nuvM76UqvmqulV1apuqJAGalpwRBBQYP5SLt7X1eb6ndvsCGWcqSqa+yuwCs1d2alMuxcYhq0+vfY\nMEO96ksMaXAoZncJZtkQA3G7AzLVq2HnZe8P9AdDESUSg7L/K56RbuukK54eV8pAl9oPbdL//Ohf\n9d+7C/RX5fOVmVqjwglZNkSBgrsW+/qSyrLeGW7hdUsOJmy35iFrXPChGuwGysH+Xjs/GwJhMGZD\nQiVsvZgyCwrscwtHbLilgUSfEobQa0MixWxoh1SfUNKNbJ/efpK0oRIGbb9+Lv1Wx6FYqrIy7a5H\n23majcXMggACCCCAwHgSCG888BDAgwOf58B7EvhzZWWlfMgfDxOeeOIJffSjH9WnP/1pvfvd79bc\nuXODyZR9O99HuJ/w+fTPcbjXXtjD0fcT1scDDQ8xVq9erT/50z/TzOnTdJUFG0uWLAnqmpuba3/3\nZEeTIntwMLpup1+nc7yl+fufT9Ey+qYFe3PYZuQPrOM+i7Y5aWF4u5GtT7KWfWr/H56A2nulnP+/\nX4KenFaN81+Tk5DxNgIIIIAAAudYwEadCP7zeI4Py+EQQAABBMalgP8nwX4c9jVv0L5ND+uzX00q\no2ymvv61tyrWsFrb1v5CP91RoMThg8pq2ad9/UPKnjRL0xbdrJtWztL8qQXW7r9fz/z4ZT16zwZV\nXT6ghrYmvbDxkFIyp1tvgTn6yP++VXUTbbLi3gb94lu3qzenSkU3/KbmVReoJN6uzoPP6OfP9ekX\nL8b0ex/M0KYNa/RXX/gL9aUu1GBagSZXxPTWj/y+rrz2Jl1WaaFFemrQMJ9s36o1zzymv7z9n3S4\nKa597TmaP0W64f0f1xU33qq5ua/q4MvP6vv/+YgODfarO6VAA4PzdMuHrtdb37FY5Zm9at73itb9\n/Id69IV67TzQYT+aB1U5fYXq5l2pD71nngbq11ud/1T//fQR/bIhVYunTlL11Bs1Y/o8/da707V1\nW5O+fddh/d5nb9HiRVOUa55HNv1ce7au0Wq9XYvnVOuK2phe+Ml/6bk1L2h9S4Z6O9uVU1ShGz76\nf7RsRqGq0hv08+//m17etEfr9lgPBxsGqmLiZN30gf+txbOqVVOSotZXn9fL617UD+99TI0WPAzl\nlCl/+rv0kVuW6Kp5E4If+2feqDIur1AqhQACCCBwgQr4z05/eFjgQxX1280IPjlyR0dH8Dhy5Ij2\n7dunrVu36tChQ0Gjtvc8WDB/vlasWBHMfTCW/23r6urS9u3b9dhjj2n37t06cOCAfMLmurpp9piq\nCRMmBCGGD7Hk4YHP1xDMbWBDKoXDKl2gX815qrb9zWnfcn9ieCiqNLsBhQb78/RVcFgEEEAAAQRO\nIkCPg5PA8DYCCCCAwCgB+6Hf3VKvfev/Un/zg+WalYhp0ZxKDaQ26PCmFt23VaqpzlNtTYGyBvyu\n/5f1ne99SdcP3aLeTLsTLz2hvasf0J6NB1S3cqndPV+pmswe7Xj062or+4CqFn1IdZX5SqbYXfZt\nO7V9Y4f+8a/T9WvvnK4h+YTGZXaHfaoGU6xngN3a7yMnjYyeNFxJ/+1py5DNXzDksygnh4clStpd\n/km713+gv1U7Xlir7U/9Qmu291gYUKTs+IB2PPCgnp9VqaIpE3Td3Lh6ejpseKa9au+2O/dzc5Sr\nJu187hkbOqFLy6+oUmaHNdLb/uOJAWXaD90U6x1hMzdbBwwb2qn9oA7YHYo/+v463fab12q2TYeQ\nY7Xvatqv/Zu+r0eGFmtChZ1HdVL1W9bo6f93t+7WRNXNmqQrVpYGPQfaGvZKXev09DNrtdGKOZMm\nKaNzv5r2turHD72gXJvcuTS3WDuffVIbn1qrJ3cMaGptugozYmps6VCf9VIY/hnO3XLDVwT/IoAA\nAgiMF4Gw0d97DwR36VvFwjDB6+iN794Y7w+faHjTK5u0bu1addgwQSnWLbBqUpV86CJvtPeHDxV0\nJov3LOjs7AweHl4cPnxYmzZt0pNPPhkMo+THmjdvnmpqalRRURH0ivCeBv4YHRr4+Vx4S9JuXGhR\ny6F6HQvjaQYAAEAASURBVOmwHqNZBZpUM8F6haYo7r0/bek4ctA+3694eZ2yCopVkOH3lsTe8FST\nFgwN2NwQiaTd2BGzGzwybNLoE2w3ZH+bdduwmOs3NSgjp0DT581VjoUHaW98iDesw5tdITlkf9/Z\n9dDdZx1p7TrMzk4nxHiziKyPAAIIIHBRChAcXJRfKyeFAAIInH2BlFQbfie+SNq1Rpd/4o/11ls/\nqFlZO7Vl/bP6yO9+Udvft0hzlszTVB+yKL1DpepRT/m1Wr5yrt52ebZW//c39PLqJ/QPd96gipxl\nmrLYhvcpWKg0G54gNWV0c7f9WEum2wnYsAXlV+mq6kp95fPN+vp3bFLF8un67J9er9rJlcrLzpRl\nEsESs0AhpXCu5l+eoi/84V7d/dMhffPhMv3JX79LCxcUKc16N/zH7T/SK7tSddPv/5nefkWNytMa\n9dKyz+uJHa/ob/4pR3P/Yp4yMstUPOP9+vivzFVJuY19nNijh757j+7+ky9o/UffqXkz63TTb/2+\nNhz5Z3VkZeuGX/+0rl80R7PL7Yd22y9tqCEbN8iGdEpamGCjCVkriP3INreUjErl9tuQQ8HP0JgN\nf5SrgstrpXUr9eGP3ax33rJMkyrKdej5R/TUg7+hF4b+SpfdukS/9b4lymh9Udte3qjrP/CfmlmT\npprJi/XLL39XTcUzdfNvf1q3XVWpKSVx7djTrclVecMe/NwNHPgHAQQQQGB8CYQNz+FkwtYWHSze\n+O4P743gDfV+p//8efP1/PPPa/369br99tt14403auHChUHvA++JMHny5CCA8O18v+G+fYejO9X7\n+6Nfe9lDg7a2Nm3cuDHY/1NPPRUMTVRgwwb65McLFizQ1KlTg4AiPz//mLDCh1QKexpciKGBn38s\nNqQjdpPHg3/3MX3932s05UPv0+f++jc0typbxWl250NsUDvX/UI/eftHVXHnQ5q14jpdUWV/h9nf\nNbb5CZfQf9Bupmg9uF2tA/nqjpdoxgQLeSw8sKOO/HXiO7Dera3b9erLP9TKG7+ia9/7YX39H/9N\n00uzlJtiw1id5O+Y8BhegdHf6fEVOuF6fo1EKw4PVeUvfd3Bvg71dDZr8z776zMvVzOmlY8MoTl6\nm2hjCggggAACCFwyAgQHl8xXzYkigAACpycw/PvQfmDZmPrxeIaW3fYHmrfEAoEFdarMyFZ/c4Pm\n264T7X061NyjKaV217+y1acZWnHlXC1aPFvVE1OUWLbIAoGYvvbdNrXfZneiKcsa1/uCRgL/iRj9\nDvVeAyPdCZI2DXKuzZ8wqbLE7iyMKS27RBNtqIDi/GybC8B/7A2fU/hDMDMzS1UTy1VUaJMk9BRr\n4sSJKskdVEdLo9qsd8DejhZlH9quza90qsH+t8uGJtqzI0cbW+vU3Z+tsspiLbo8aXM3dKl5f5MO\ndx/Q/sON6rTD9A8MKSU9Q/l5NlSBhQaldsdhWeUklVeUqKSgR50d1jBhDR6yM7dS9OPUzyxpcxx4\nkBCco/3i7u/sVUHxFH3oj2/V0hULNMOCkIx4Qvt7unVwp2z4phY1HD6gTS9aWNO+Xru2bbT9PmCT\nPt+qhs5UFS2foEPbd2j1L+/X1MIblDJvlqprKlVoLoFFCDLMw78IIIAAAgiMG4GwUdcb3b3nQfjf\n/+EGbftvvb2XkZEZ3NXvDfj+3/L5NlyR9w7wSYqfeeaZoLHfhwwqKioKJiouKCyw/z7nB/Mk+Pb+\n8P17QOCPcFgkDwtaWlqC/bS3taujsyPYr+/n/e9/f9CjoaSkRFVVVSotK7W5loZ7GPgcDN7TwOdn\nCEMDP4/wXMYN7ilVxMVt3qcB+9ulda9KamNqb9msR5/ZpsKVdSqebPNE+d8u9jebT1+dGLQeBPa3\n2fDi5zxSfM2TrxPTUKJLLVv/Rxs75mpfxhWaUp5nf/GNboAf3kE8q1IlU27QP//jFOVXTFJlftzm\nr/KdntqQRadqf+L1jj2PWKJRXQ0v6/77UzVp6hTVzai0v0BZEEAAAQQQQIDggGsAAQQQQOB1BYZ/\n3tkPQZvkOM0mE65ZcrPqps/XtPJc+/FoP6xLqnSd7SGtp1+N7b0aKraG/1i2BQPTbFLDyZo2tUQZ\n1mg/2cYIbm7rlbZ1Wdd0m/zXjzry49N/TkY/RO29sOyN7j4hcGamTW9styX6j/XM9DTrRu8/K4d/\noAaVH9lPiq2bZT/s4xnW13zAfoDahMZpyT4N9rSpzeq/t7tVVUe26OWOfcpOtKurLVN9yUzN9eGU\nbCbnmM1pEO9v0vYd9drf0GwRQJf21jfasbyqNl20dV9Pt0aEDO/GbkMmZfuExNaIkJpmYUFYafup\nGZxPUDH/52iIEL6V6OxXgTVITH37Ek2bVaWCbD+BLg309qtps5R9Vbc62/frpacPaqBvq5pb6+V9\nCdLj1giSzNLUa5arPWeN/u5vb1d1WkLtjT1aed0VyvQGDnMaJRMekmcEEEAAAQTGlYD/dzPseeBD\n2XhD///P3nkA2FWWef9/+73Te+8lySST3jukQ2iyIIoVQVHRta5l1WU/67qW1d1VkVU+lQU+pAlS\nFAIkhEAC6b1n0qdkWqbdfr/n/945k0k1ICHJzHOSM+fcU97znt+Ze+Z9n//7PA8/c+bfe7f8Daex\n3u/3g/kHmLD44MGDZrl7925s3LgRU6ZMMUZ+GvqZZJliAj0CWLblWUDhgDkVWlpacOSI5DCScpjL\ngOsLFixAeXk5iouLUV1djezsbPN3nWVwpmDAkEicGZ6IggTrdzl6Gpx4+GxzMMxiEMEOwJcSwNH2\nXbj38RcxutCLKsld5Ys3fEx7wgyAEE9Kti5C/k5pw3Wgtb0bgVBEEhvbkJgi4aNklH5qklfyXMnA\niyM7sP61b+OVhk9gnQz+GJcbwtDyLKRlpcAlCZCtwE7OxAyk5Q/H+BG5cItXR4rkrIp0t8rz7kFL\nt3ighP3i+BBERyAKT4J4fch1UpMllBUbgbEQ2pulrdTeA0+SDf4Af0ekjekQgScpGZlZqXKcCBBy\n/vHGw9KASoIzJVvCVEp7Ts6NiLhxrF1EEVFG8rKcaDqyExve/Cu+9+0EXPf+GoyfmIzSwnwkSbvK\nx3J625knGOqaElACSkAJKIHBQUCFg8HxnPUulYASUAJvnwD7Z+Yfu5myJqPqo9KBpKu6TWLXOsRw\nnimle8X4LbZ0WthPmoxLuxwrwXtk5tg1609P/ECHGArcEsuYRgN2zNghdDq4j+bv+M+ohDLyJNtk\nluKtHmf/C/VayqX/ykBBch2ZzA85X+obEqNBSziEpJJCTJg0DWXS8UyUI0OhyZhpz4LTly3hfo5j\n36qVuGfeh9D9/s8jsaoGCyZWwZ+3F9KvNiPPaISISC8zKCPvAnJNU8N4Nc11YhLPF0iBjQn+5DYp\nIDikwo7ee2O1OEVke1RiCDslVEC8omQiUojkjnAcAMo/MAIFZeWYVOgST4+xZrTfFYu/hNLqYSgp\nyoAv57OoHHc1qmpn4tXfP4sVv1+G31z1YfzbP1+FRTOGSO4FESsIUycloASUgBJQApcggf5/o2iE\np1DAbVyncZ6ivDW631oOHToUpaWlGD9+vBETmFiZYgDzE9ATgfkJ6FnAifkK2trajJhA4z+N/hQh\nKCzMmDED11xzjUl0THHAEgYsrwIea23jfn5mHSwvBpvUkVP/ezAbLpsf8YYLnSSj3cCYmVOR2OXD\nU//3y9iwoALFw4dhdHa85cdBHmz7mSaXtFkad6/CyiUP47sSVmj97vgNX/upH+O6q+fhHxaOQMf2\nF/Han76HT/9hCFr334uS9Hsx+2dz8eHP3oIv/8tHUZHhQqK06ejNYEM3ejoO4uHvP4302qH4h6/l\nIrTjKexbvxS/WpkC99ZNcK97GY/IZRbe+k+YMPNafPCaURhW5EK4ex+WPbIKj396OYZ/Fdi6bzt+\n/8eVcuTNuO0fr8Edn/sHjCiVkJit+/HU165CZPwXUXj1xzC1RJ53uF7CNL2MXz4Ww+56G773KQ+e\nee4l/OPXfiNJsJOx7NkOPPUQcPf/PIkr5swz53ikXaeTElACSkAJKIHBSMCy3gzGe9d7VgJKQAko\ngb9FoNcobpmgzUfzQX6YJWMSy8hAKUcWvaZ+WY/5ZdtBHDjYhPTsDKRnhnGkbj8O7pI4PAXjxStA\nOuBytEOC5fbIKLFD9W3oKZFRhdFW7JJkiE0NMmx+TFW8TLloREIXRQIyus3fJceHEEyQMASynd4I\nVnVO3Ap9A2Qy7u5STad4HXgTkSIVTLdLwkWvhDsqyUF+kgOhoN+M4I+Kld8ZPIDm5nr8UU69tbwK\noyeNQnWxjEhLdeO4bGOZNhEB7C63dHrF40BiD4VFjAjJiD2GVnInpYt4wj+r69DT3SOGjACSovU4\neOAotmxpQrg0LLkcZLdMfXW2MJqtYigRz4ek8cARKhXiY1BUWQofucq1erpDSMmWkZROES663fCl\nF2Pc7IWwdbQjsWQLHn1gN5o/eVy8JETEMeXpDyWgBJSAElAClz4BGuA50zBvrVsCArcFAgFjvKcx\nn54D1kyRgDkJrBBG9EzgNnoYcKKgUFdXZxIcM18BhQOKAxQPmPiYuQvoPWBECvnb7vbExQpLOOCS\nggZnyxPCEgus5aVP9+w1jMogiHALUFg9AUkyEMS18gHU1x3CqjUHMHROlrlnns22D8MP9TQ3Sntm\nB15cdghjr/4mFqY7kBhpxbY3N2D/6lTsFi/TFHsm8qvm4vraJ7CnZCbaE4bgqqoqjBlXgiT3CW8D\nUysRIqJRCXNZdwDhwiz4xYMh1NUm+RE24blXorhqWCXKPvUFfDFah0OtB/Hc889h1sQCFErISo94\nNhw/vh/r8Vd4j/0DUkpn4Z++Ogl7VryB44c24NW145GZUIR8WwhN2/YgXNaBBL94GoiXKcQLIdB5\nDIf2xbD1YAJinjIUl1TgfeIFumprKsqHZmHmzDJpA+YizRsf2HJ2irpHCSgBJaAElMDAJqDCwcB+\nvnp3SkAJKIG3SYAWbRn15xLjvriVG1O3fGY4HyfdzI3l+0TR/Bj3GIjvcMgYfTs2YcVrGyUkURip\ntQ688cqbWP3KCgy9ch5SsxLhFiO6T2Lyd7d1YOOaLRiX34WIuwEv/Oln2NN0K6YPGy4eDFIe3Qgi\nkriuuxkdjQdw4NARqYN05nziji6j1kzn3Vj1WR9enyMWZSkJi+kWYbP5kJCajTIJK9QmI+uajwXg\nGOpFcqoXofZOtMtwuu6Q5GDokFwGPX60oBZDRtZgwrhqZHVvEKEgCnFyFw8BKVkSHTt9ycj2JCIz\n1Im2lno0NvqQLVwy0yXkUGqSHHkITYcOYff2JBEVNmLVqi24/w+bMORrIeHJ+omnAcUW8aqw0Mbr\n7UZShpQlCSOW7GtEepbIFZ5UcZMXHwoRTdqa2hEWESMctmPnpu0SMikReZKseeSciXBlSEf4gYMi\nrATAsZaePh7yQScloASUgBJQApcogf4GeIoFnCzRwDLaUyigeEBRgDMFAm6jQJCUlCSDCyJmZmJl\nrnN7Tk6OMfivWLHC5EiYMGGC8SKwRAAKEtZseRRQQOi/bh3L+rCeVv0uUZRvoVpsi3BQgjSvtoif\nZP4IyUOQiJE3AcvqtuL/PpCGaydew9aK/GP7TgZa9LTI4IoleG3lBvzqT8l4ePnHMKk2Halde/CH\nuv+DnUv/jOVjZ+KqSWMwcb6IOYdeworW6diSNB933TIcVcXpIsxI3glzZTaoWIHeenh7EHPIIAxu\nlvaR3e4GDr6Omrs+hQUL50vGrNV44YWX8cev/AB7PnwVKoYUopjl2DukfkfRnj4VN107BjNqbHgl\nrQmvv/EmvvrgKIwq9iKvUkZfSBPJJm0uJoRmG8wEkIy5EA3KgI5YCnx5UzFrthvZznas/5YLw8fU\n4K4vLpAQRhLuSIQlcYrVSQkoASWgBJTAoCWgwsGgffR640pACSiBcxCQ3mRUkuY11UfhlaS9DNEj\nQ/7FeL8HTQzVE5bPvcbpiOQO4Ih8SHz+kIy8N8kNZWezbFr66C/w2pJkPJnrxI6nGuGpmofPfmUy\nRgwrkvBEIUxYfCNal63Aj+7+PhqXpSInOSJJg6egQWLUNjR0IMy8CsmSfFji7dakL8MDv/8Vvnbo\nUSy+/euYMWcRJha4kSAxcfvs5BJCKRrxo0eSD2OXJF42MXlTJP5tBebedBXw5JN44Hvfwsoh6WJs\ncCMoSQHzx38Aw6csxPunDUV5RRtuH7kZj//qO3jioRykRDxofm05UuVeApLgOBxxiwdDLqrGV2H7\nzu/i6z9sxoKa6zB2zGR84fYalJSV4RvzgRf/+F949OEU5IpocnjZc6SD/e3CRxIsU8wIdjajuyWC\ngHyO5xuMp1MuGjYBM27+KTb8+4NY/ZtnsGNlJbwOSUrt9KKhfQhu/8w8zJ5Vgt2v3IvNWw9hWyQT\n0ZatUq8ETL/js6goKzJ1jbs0mMvqDyWgBJSAElAClwUByzhv2hG9hnrLI4AG/WBIvAnYBun1KrDE\nA0s4oGDAmSJDZWWlGTHPRMr19fXYt2+f5F0agYyMDLOdooElDFihkKxtXFp5DKw6Dci/q/T0kN+M\nHr8LRRkywv7an2HzIzLI40f3Y93nxsHWFkBahQSYlDA9PZJj4si+jehs2Sln7MPapU+jZW8anP6j\neHPDWhzpHobd649gQnUOKvLFy1M8O1JCkpcgMU08PBLh9YhvqjTW5JKnTTHTdoxvjoYC4r2ZgYm3\n/QyTx0/F5CG5SMAolGysw2w5pKfFj8bWbhSm2CXsY7IIEbNxw9VjMLq2QgaU+CWc0Qx0RsW79Rsd\n6P60eJWK/2tUBBL+TrEpy/Yif8RMyE0Jbcnt0hBj/qz0NImHKcKFR/IhpEnOhgQZ4WKXZtsZqhyv\nrP5UAkpACSgBJTAICKhwMAgest6iElACSuC8CfT2juyuFCRnD8eCa8TjILFAOlQO2CQ0TlHtx7A4\nmofCLI8ZfSc9LCSk5WDUV94Pb3UxslNkdJoMo4/I8C4WNWpsjSS088IlAsCMO2Yhu6AGM0cXoTA7\nQSIJBVE6ehZGhVNxR+sbJtyPU7wCaieJSNCVIaPbMpEsoXucYjRPyhmCaVdMhystFzsb2yW5Xfw6\np96X3SkJDNOHYtjoED7zT0lI9vHPnOQNcGeIsX8KOoMxNNpWoz0soX/Ei8GbVYn01ERkpEg4gsQs\n5JcMww2f/Bpe39WKQ81B2NxFGPKhXBRlhVBRnIEMyarnkPqUTZiKieFv4Y61dXCl+iQpsYRWcqZI\nCKShmPeRb8O2sQEHGnrkutkYNqxa3OUl2aPcd366xNuVvnPR+LlwD41JguQkcd2Pj79jRzYpuxwl\nI+fiioWNyK1rwG5xh4iKeOHyJqM8U5L6iZeBW8ItZeYJ6w4H6huk01s4GamZORg7bxzKi7PMaD4z\nmu5UOPpZCSgBJaAElMAlTsDyQLAM9hzlTyO+ZdS3PAoskaC/lwG3UUygRwLDErEM5kPo6emREDtb\nwBwJDFNklWUJBP2XvJ4196/LJY7tLVbPmM/jVvQEyQ0VisKVkIm8ktkoL6sXv8sH8Mb6HUg4ehiS\nnxhehosUsaajaZ/kJGBAxELE/G3oaJXBD8EIcsdfiUxvPmzStvNJCErmv3JKmEiX0x2fJQGW+GvE\njfZWTXurYH00Sxr0xcrvcPuQXzkBuTmFSJM2pKQvRnpyBsQhUyobRneA2azoCSptUUiOqtIsZKVL\nWzMsnySMUWYuh7P0iMAUlvao5IqSg+O/T/GQWBQv6Jlqmry99WDoS7eIB54U8QiVtqdL7oO1PpPQ\nwWropASUgBJQAkpgsBBQ4WCwPGm9TyWgBJTAeREw3Si4UspQUFOCL1bxJJt0pqTDN/RK5AyZhfHS\nCWOInXiH2oH86nG4+Tu/lZwC4lpuE7fvsFPCE4mXgCSo+/iX7kb10EJkSM/T7vKK0dwtHgx0+ef5\nbiQXTcYVeeMwbe77xFtBDOgy0itB8h/ExKgfE591t8SW5Vh8T3I15n7wc5j13jAdG8RQz2SFkkix\n956szj2THGeUL8It4sN+k5zv6TXK26VDmFwwCtNvGI7Jiz8Ef4+ENZBRZC4JS+CSclwiRNgl7BFK\nxuKqj9dijoT8CUtH2e4RQ7+4tjMnnt3p6Q3HBBSPWYj8EXMkWZ/cl9sLp4yE9NCVPXE0Zt4yAuOv\n6zTlO92JIpCI+CIVjbADLStOufkZH/68qblNtlmdUrO0J8OXVYsbPvOvWCwjK/2Sg4FpmdkJ93gZ\na1kECKnLwtvuxlwTukHi9dql7qJG+LwiapjYR2TbC0YXSkAJKAEloAQuMwLW33RWm0Z8JiN2iPWX\nAgJHjlMssJZct2aKBpytcEYUGWbPno3Vq1fjt7/9LRYtWmTCFVnhiCgYmPLlj6a15LWt61vLywzf\neVS3t5HAhbEG9EjDQXJPJY7AZEmM/JnPVuC+h59HcOd+lB8BpnUzaJG0iWIheRbSMMwuw5jJ01GS\nL+EZJe9UdMoM8eyUsEU5ZcjPTJTExW1i1Je8CDTv947sN5Xq3zbheq/Rvn+FGUwoIs84LHkIIuLp\nGZ/ibbUM+eBJlGfVFzqIYYckL4KIF9JkM14EoZCEsaLaId4Ipi3E5yntJv4OOWWmisB2Jdt2NhvP\nj0/murI7JUO8DxL56cS+/tXuPVwXSkAJKAEloAQGDQEVDgbNo9YbVQJKQAm8FQLSTZKYtmJX75sY\nd1bG7psR7X0bZYVJ8zg6zExRCWsk3gX+QIekCJbepogJ3gSfJMsTDwTTg+t/Zvxcp8sjsf95IenK\nSQ/OHHbSXyfWRYoSbwIZtAax5cePObmo3k/xekseQzG395/ihgCHGOo5e2QAm7mWdBJPTDxX7lDq\nkyDzuSaycIlS4HLLcf3vSwz3DonNm5ycJqdLeWY+vSQKKGecpCz+Yx04e8TDgD1eltR/sss9uDl7\nLWD99+q6ElACSkAJKIGBQYBtB/M3kEuZKRjQyM8lJ0tE4GeGHrI8ErjO4ydOnIjubklwJNPGjRtN\nUmTmO6B4MLjEAoOg94dlLpePNKqbrfLT5kRJ7WhM9n8CS156GltDTdKWA0aKOMO2XE7ZWCRtPgY0\ntYiTZQHySwsl51MMne1NCMXEmu9jEmkph2EjA20ISHij49FuBII9IgJIyCDJK8CBGPJYaJfvm8xn\n65OpTLwt1PvkZU987USTjZ+jIiZ1yL438ObavfCJR+iIrB5sWvkmtqyuA8YsQkKieCHIceJEiyMN\nzejcfgBTCnPRdXQvlj3zOJrbpsk9FLO5i5h4pEbEQ+F4Qzvam3NxvNsvA0J8cEvlGKrJVMuqoy6V\ngBJQAkpACQwiAieZZgbRfeutKgEloASUwHkQ6O2X97ONcwTWia6cVYTpwJueH3uEXqSkZeCG2koT\nH9bB2LLs7ZnC5Nwz9L5ikiCP20+M/oofdNKh0sk0VzcbT9pjVaNveXq9+3YZY4MxRLAIOZC5+U66\nI54slTF9WqsgOZTnnDydOE4GrbGQ3okf4t1by7DBHSedb5V7WplWEebqco7VTZZ6msv1XuSk82UH\nDz9bWb1F6kIJKAEloASUwOVMIP63Oy4e8D74N5bGf2udHgkUEuhJYE0+nw9FRUWYN28etm/fjqys\nLIwePdr8Te4vHFjHD6YlWxR2Gedg2idsyAhPX1YJCodMwIi8J9Dmj2CJHBOR9oUvIRkZpaMl5OR6\nIP0wDh84gAyvDBRJtqGt4aA4LCRKPoRspCZ6JKSiXTwQChA73ILGpu3YuCGCYJeEaywpkfCM9Lw0\njZY+1HYJh8nQQWxHsT1m54AUtmlYwd4pJp951om2jngNSMjLHhzGmyIWeB0tCBSG8dprO1B32IWr\nF+QjNT1J6uJHzrBJONjagLVvvoH1GXmINGzBxi3L4Y+Nl1CVcVHAJl6lLlcSMjy70F6/A+vXrUN1\ndTWy0zORlcQ2ar/KWJXSpRJQAkpACSiBQUDAskgMglvVW1QCSkAJKIG3SsD0207qK51kYu8rznTm\n5ZPNLiP8vCWYfe2N+NEjd2NcZQ4yZXC9XQqKd/j7Tjlp5UR/jOXHr3HSZXm0bIh33E7bc1JZ5lBz\n7GmbzYaTOn+sFwvuP/VWhlvjdZYjTlSw35Hx88zPk4o48eGs57O8M5bZW/xp+0+pw0n7/0ZZ/Wqs\nq0pACSgBJaAELncC1t9WGv6tmaKBlQuBwgE9CrxeCZEo20vEYH3NNdegsbERGzZsQHNzswlnRA5n\n/vt+uRM6v/rTQzRcBwnvFBZvAOucDCRm1uCaT8zFhCmSAEEmBh1KTM1DztB5mDZxKL4y7TF84cML\nMW/KSEk4XYvpc67CN398LzYdbEFHICrekIkoGDkfEf8erLjnNty4+KP47n88gf0dkn+i7zosWT6I\nd0LbWvEGOB6IJyqOyDLYgqYAQ0paB4s3QDiETjkjaOoaH0zBEjbL/P/+6wu4633XYcbMG/H1e7dj\nn3MqPnbzJFSV54uHaQam3PgR5GQdw59/cBuuvuIqfPRrX8aRnBtwOOCWnA3dEuZI6pySh0zJczUp\nZQn2PvpdvGfeLPzh2dexriEooTStevCKOikBJaAElIASGFwETgzHGFz3rXerBJSAElACF4QAjeYe\npGfnIC0zHo/4glxGC1UCSkAJKAEloASUQD8ClqDATfRGcEu8RYYuys3NRW1tLdauXWtEg1dffRUz\nZ86UEeVDxFgdNSPc+xUz4FfjAyZckqpgOK568Bdw14xEZoaEcuzNk+ROyED11PfgmoxxKJrWgDET\nqlEsyYc9CbmoHj0TN3/uIQy5pgVd/pDEkZRxiOLlkVNYihEFKUgWjwK7K1HyTc3G3GtzZblAPDvT\nUVhWiZwECYFpDVtkczGWBF9KJe78w+fgkZH9RaleRGrmICNvNL4eqURFvoRrNJNLvCDG4Pr//U/4\nRg9FVgZzOjkQRhIqUYObvn0bMjKSkCBCSNSWh4KyKkyqzkBGgghL0QTk18zFFZFi/KzwShng4hQR\nJEnqU4jr2xPhc6ciRZIh2yXHVFJWDd7z2e9hwnvbcFRUiqFjqlCeJtc610CP3hrqQgkoASWgBJTA\nQCVgk0aVSugD9enqfSkBJaAELiIB/nXRvtZFfAB6aSWgBJSAElACg5AAu7cUDJgo2e/3G++C1tZW\nPPTQQ1i/fr3xUvjUpz6FK664wqzTK2HQeh6IcMJcSmechGNUZiscVN8x5BsIiEdA1IQxYj6J/uGh\nrONiktw4Kp4CQRlQ4hSBwdWX1Ng6ondpWSMoJpxrsuoaO45w5x784ddLcN8/bca/7fh3DCmXMEmS\nGNkmuaccTvE+OaUc1iUSpveAhEWS5+1xS7pnhtKUa4uW0G8KyXEx8WywidcKBYW/Val+p+qqElAC\nSkAJKIEBSOAsrYQBeKd6S0pACSgBJfCuElDR4F3FrRdTAkpACSgBJaAEhABFABq7KQjQqM0lQxdN\nnz4dY8eOxZ/+9CfU1dWhqUmS+oq4QKFh0I6lO5towN+kXo6n/VLJdofwdEv+CIaDOpNoYE4XrwCH\n2wuvuBmILf/sE23z52Of761rjIKFiATd3c1Yge0IhMRrRIQJj1fqdAbRwKqL0836yjGuuFLApMhS\nxVMm+X1xuuW4eHLtU3bqRyWgBJSAElACg46ACgeD7pHrDSsBJaAElIASUAJKQAkoASWgBAYuAUs8\noFGbM8MWFRcXo6yszNz0rl27TL4DeiRwGrTCgbn7t/FDxAMKC+f21IgrAvGfb+Map53S65pgE+O+\nJwvlQ2rxzc/cgJxkEQN4rIhFZ5966xKv9onDuPkMU+/tnWGPblICSkAJKAElMLgIaKiiwfW89W6V\ngBJQAkpACSgBJaAElIASUAIDnkCUI9MlZFFAwur09PQY74ItW7bg/vvvR0dHB3JycvCNb3wDRUVF\nRjigl8K5DeEDHtllcoMSXgkRdHX0wB8IIy09TbxKziUaXCa3pdVUAkpACSgBJXAJEtC/sJfgQ9Eq\nKQEloASUgBJQAkpACSgBJaAElMDbJ2B5HTBUET0OuGSi5MWLFyM7Oxvr1q3Dzp07cezYMXORQR2y\n6O1jvghn0oThhC8pCWkZqSoaXIQnoJdUAkpACSiBwUNAhYPB86z1TpWAElACSkAJKAEloASUgBJQ\nAoOCAIUDzhQMGK6Iy5SUFFQPqTYCQn19PTZt2oTDhw8bzwQNV3Q5/VpIHgvJeeA4PUnB5XQTWlcl\noASUgBJQApc8ARUOLvlHpBVUAkpACSgBJaAElIASUAJKQAkogbdKoL9wQK8DJvNNTUlFeXk5pk2b\nZhIlb9682QgHb7VsPV4JKAEloASUgBJQAgOdgAoHA/0J6/0pASWgBJSAElACSkAJKAEloAQGKQFL\nPLBCFlE8GDp0KGbOnIkjR45g9+7d2LFjh8l7QETqeTBIf1H0tpWAElACSkAJKIHTCDhP26IblIAS\nUAJKQAkoASWgBJSAElACSkAJXOYEKBpwssQDZ2/YIiZEDgQDyMjIQF1dHVavXo3U1FQTysi6Zetc\n6/PAW8ZEJJE0w+EQTCJpyTnsdLrgcDokDNBFuFtWpvd5xa8erx+FHAk6BdtFqdRF4KCXVAJKQAko\nASVwCRFQj4NL6GFoVZSAElACSkAJKAEloASUgBJQAkrgnSXQJxy4XHDJzLBFaalpWLhwIcLhsAlZ\n1NTUZC46mDwObDY/6vdswOqlL+DJP72E9dsPoiUAhKNixH+3p5NEA7k4qxCLItgTQSgsIsK7XR+9\nnhJQAkpACSgBJQD1ONBfAiWgBJSAElACSkAJKAEloASUgBIYkAQszwG7XZLpiscBhQOOsE9KSsL4\n8ePh9/vx4IMP4tZbb0VBQQFycnLAYwf6FPa34njTDqxcsQZbdjQh7E6DL68QmcUxpDjFTP+ujfAX\nYSAYQndHD5wJiXCKqON2AFF/A1qPHcFrqw8ht6QcNaNHIkG2Oy+GN8RA/2XQ+1MCSkAJKAElcBYC\nA79FdJYb181KQAkoASWgBJSAElACSkAJKAElMPAJUDzoLxw4nE4kJiZi9OjRqKqqMgBWrVqFNWvW\nIBgMmjwHA9bzgCGBZOpuOYTdr/wW9//uWfzrA9twvKcV3XLvnTLCP9LrcXDSKH85j0x6T5cSrM9n\nWJor9P9xhmN6ywP86Dx+DDs3b8fRpg60+0U0kAsH27Zjz+r/wvU3Xo8H//wsDneEEZRwSue67klX\n7Kvv6dfuf5yuKwEloASUgBJQAmcn4PhXmc6+W/coASWgBJSAElACSkAJKAEloASUgBIYGAQoIvQX\nBbq7u5Gbm4s9e/aYGxw5ciSYQJlCg+WtMDDuvPcuzIh9G3paDuLoxodwwDsPMxZdi4+/bxaGV5ci\nO82HJHd8fOFJg/uFG3nI/76C4p9PbO/7bB3St7SOOXUpSkC0CZvXv4mf/OTXiOZUwZ1RiKJUO9zy\nDBKSKzFu4jxMmjgRlWVF8InHgaOvHlIW//X73Hc5Wem/3az329b/OF1XAkpACSgBJaAEzk5AQxWd\nnY3uUQJKQAkoASWgBJSAElACSkAJKIEBQoAGZMvzwCleB8xvwNBE9DzYtm07du/ejQMHDsDj8SA9\nPd0IDDxnIE0xCdMU7GpBw5E6bN/7BrqjC5DscUsegWS4bWE4wy3YtrcbKalJyMlLE0O9jPEP9iDQ\n0YDOWBLCjiTkpsnxnRLqqKUBXVEv/MGIHNOFUFTCQXkSkF9YjCSfGx5aG2Jh+LuOo+1YIzoCMYQi\nduHqQIokpk5J9iLUsBk71q/Aw08+hkj1VPjtXnhbfPDZ/QiFgJyi4cjLy0OiS8IUIYJgt3gltDag\nvSPuHRGzO+BLTEFSSjoyUhPg84jgEwugpb5T6tcFT1oM3T3i1dARgDshE8mpKcjOToFLQjG9a9GY\nBtIvkN6LElACSkAJDCoCNhltcZIH4qC6e71ZJaAElIASUAJKQAkoASWgBJSAEhgUBOKhdmJGMAiJ\nVZr5Dehx0NDQgPvuuw91dXUm78F1111nljyeeREGxsRuvw0hfyd2vvhjvPjSEnzupxtkWyc8GI0A\nFuPX91Zg1Agvpk5/Hd/776vxgdsWIT/BDv/hLdjx4r/izcB1OJw6GV+9rgAN6/+Kp//jJqxx3Iy1\nhzqxbflzBtO0udfiE1//CaaNLEV1jgOxngPYvmY5HvnFx7FkdRDLd/OwWnzpB1/FnHkTcPj3n8Ka\nVUvx64Ol8NXvR48pJf4juWIUho75CD5/+zzcsKgWibEW7N/yKp76w9fx6trt+OPL8eNmv+fTGDN1\nET5y8zTUlvlg69yDp3//Ov74maWo+XI3tu7bgv/32G5UTP0cbr5hLj52x9UoThXBYaA82n7MdFUJ\nKAEloASUwDtJQD0O3kmaWpYSUAJKQAkoASWgBJSAElACSkAJXNIE+nsd0LsgLS0NEyZMMEmTH330\nUeOBUFNTA7ck6uWxnC5/z4O454Td6UJ21QzUtNnwyWt3YUd4IdKKJmDyyHEYXtGOWMdBudtNaOuY\nhs5gDNEEIBIOort1PVp6rsTRaFByIEQRCvSgeTuwz9mJxOxq3P2jeQgdXYum/bvw5NPrkeV1oyQj\nE3Urn8Ta1ZuwdO91mHDTGFyfn4LjuzciLdWN4x0xVEyai25HCvDzpzD9hg+jdFgNRhYnI9yyA/WH\n6vDjpeJh0BZAJBTEgW0v4I1lL+Oh/5Vkye+5CT+4MQ/erp3Ytb0RL//hDxhWmQWnpxLVvh50dtVh\nHR6Cq/PLKBs3CT+Z2IWXv/YcjhT68MrEUZg/Og+lGR7J1EA5RScloASUgBJQAkrgTARUODgTFd2m\nBJSAElACSkAJKAEloASUgBJQAgOKgGX87y8cMFwRBYIRI0bg+PHj+PWvf429e/ca74OysjIwpBEn\n69zLHYjD4UbO0CswCnb01D0ER+dM5NVegduuH4qk7g3Ytnqv3GJE7jcqQgpTEZublzhBaSKiOOCM\nWWZ2O5wiKqSmDkXVzLm49UNTENyXjXUvduLD39yOhZPLERiXiC1LH8TWXUloG/IBLLhhHiYMS8Xx\nncvRGM5Dmz0JY66cK2U7UYSnMHriFRg/dz4WjcpA+MhybH5zGX78ghthCYUUCfux540XsP7F1Xi9\n4YO4fd5VuHpRJXwdG/HSn5/Dyt99G2u33IjUghxUDJHnZQ8hUaqeWD4bV8wfhvHZHcCSZ1DXvBPL\nNhzFhLJ0IxyocsAHrJMSUAJKQAkogTMTUOHgzFx0qxJQAkpACSgBJaAElIASUAJKQAkMMAKWAMAQ\nRBQFXC6XyWnAOPqlpaWYPn06NmzYYLwPPvrRjyIhQazjA2iKj7B3wu7wITExFZ6o5DaQvAQJTgcc\nMvY+Hsk4yjWRFnonOSkmuQpMqKfeTWHxRgisBKb/93QMnzYNBWnJiBUUoblyjBzhk9QGIjxEAji2\nPwKfrxAfvH42yktzkZHsQvKIWciNuShPIMneJfuTUCxnpSQlIzk5TXIj+JCQmGg+Y69DhIMwouFu\nNB0KwpVYibv/dz5GjSlDrs8Dm28shg2rwx13AltsQTQ1dSJabUPYliylL8DVc4ZjRE05kkJNmHBd\nLbxNqVgeoSgiqohOSkAJKAEloASUwDkJ9LUFznmU7lQCSkAJKAEloASUgBJQAkpACSgBJTAACFA8\n4EzPA4oH9Djwer3Izc3F/PnzjVF5zZo1aGxsRE9PT9xgPkBSA1r+AjabXe6fAoJTRuc7DAvmgTYe\nBvAKH26Lh/EhK4d8sMuSGFgGlzw2LTMF6TJ7XE54vB54fBznD2EYk2OiCHR2weZwISMnFQmSMJle\nC56EVBEtEpCSKJ+Ff0zqwrIcUheHfHYwcbEIO3YRM3g1lsM52BMyZeWXZEryZl+8znaPiA3JKMhj\nnSQRckAEDlZAUikDyUhPSUSS1ybP2YvkLBFIJERSKBq/D3OY/lACSkAJKAEloATOSkCFg7Oi0R1K\nQAkoASWgBJSAElACSkAJKAElMBAJ9BcO6HVAESE7OxuzZ89GTk4OmOtg586daG5uNgZpM9p+gIgH\n1vMUczzEvn9iEmGAggHgMupA1BbfHwmHEOqRPANh8UKwlIfes6IS6ikiM/lEpKywGPitSUqDw+2V\nfRF09XSDCakh+1leOBJBKBwRzwSZZfR/QE5i7gSu0xkg0ltevCxeVMQEIyRE0dPtRzAYL4v7Q0E5\nv1vECpuIII4TFZTay3FRiPODqV9YPA3kv0y8R52UgBJQAkpACSiBv0VAhYO/RUj3KwEloASUgBJQ\nAkpACSgBJaAElMCAI0CxwMp3QPGAYYnodcCQRbNmzcJf/vIXbNmyxRxDw/jAmygUxO+Kt+dOSkdK\nZjYK8Dy62xpR39CBzqbdOLhzAx65Zwt2HOxCskeOl3NoSBB5wQgJVhksiYJMfLIbT4aknCg6Oo7g\nheffwKGGNkm4HEDz3pXYunkrVmxsgh9uJHh8qJST7OEA/LJfNAUx9Es5piipWEyCKNklxFE60NN+\nAE888Sr2HWhEl1yrp2Urdm7figd+JOc7PSgtSDceC7wfqYGpT1+VuGJVr7eWulACSkAJKAEloATO\nTkBzHJydje5RAkpACSgBJaAElIASUAJKQAkogQFKgEZumwyht/IdeDweJCUlobKyEpMmTcLjjz+O\n0aNHY+LEiSYcDsUFTieM45c3GHoX0Cugz7DuTUdSRhFumFsJf+MerH39dXQmN6F+y0a8vhsonhZG\nYd9gffEAIIvTEHCLzGL4pyG/fNwcHFt7AM8sX4G1VU70NKaia9fL6EwcA2fBBMlFkITklAwMLwDa\nj+zG9o2rkeGvQUmiuBA43VJW0JRnl1BDxcNHo7ixE08sWYGNtT4JqFQKR8M6rN+6D3vs0zC3NA9D\nCpJFzGgxVXCd4llg7lXqdqrXxGm3oBuUgBJQAkpACSgBQ0CFA/1FUAJKQAkoASWgBJSAElACSkAJ\nKIFBScAu8fVpX2auA84UEYYOHWryHPznf/6nCVe0efNmjBkjhm7ZT9GA3geXv3ggQ/LD+xEIhRGS\nEf5xASAdyZkVuPqaKXjyyf/GV37z332/E/myltzuh5/xiGSKRUPGpM/wP/EtZqMkRJYQQiIp+CX2\nkMudgrFzb5Lkxs8j5effwRdW/Jynmun9X/gBbq2dIxdORWpeMUbeMQ8/+va/4A3uLbsH//tvCSIC\nMDF1N/z+CByuBAyfdZ0IDU6M/cmX8a3P3mfKMT/G34Lbv/llTJswDLVFkjC5Q+QGfxCb0SahmCTX\nghxk5IxoF6IhJzpkCz0SdFICSkAJKAEloATOTcAmjR79k3luRrpXCSgBJaAElIASUAJKQAkoASWg\nBAYgAXaHOYclTn8wGBQjtRjHZd6/fz9++ctfmu0jR47ERz7yERQWFhoCxlOhb5j+5QYlbkbvaTuC\nY3VrsD9UCW9aIcZUJMPpsCPkP46GPeuwc98R7DzcJsb/dLjFMyEx0g5P0QiklAzBpOoUHN+/HXvX\nroJ3xJVILyxDUYod0Z4jaDhajyUrbRhRW4Bxo3MR8x9D/d46bFi5Ecck2YCfAYRsEZQOHY3q4WNR\nmO5GpLMRR/dswMZd9WjuAjxZozF2iAtZyRE8+3IQQ4bkYtLEAriiHTh2qA6b16xDQ2cQbQEmQ7Ah\nPbcC+aXDUFOVjSypRyzcio1v7MP+PW0Ye/UMZGUmwiNhkJp2vYpj3S4cwRCMrEhHXrqnT1S43J6i\n1lcJKAEloASUwLtBQIWDd4OyXkMJKAEloASUgBJQAkpACSgBJaAELjkC1ji6qGTkZfJeigeBQACN\njY1YtmwZ3nzzTWzbtg30PqipqTF5EJgX4fL3ODj3o2BC45AY250un8kVYB1tjd63Pp//UpIUByKS\nnNgGl89pwhydem5MkhvQQ8BOz47enUzezJBIfRus7eLxQLEH8IkniBxjDurdqQsloASUgBJQAkrg\nHSGgf17fEYxaiBJQAkpACSgBJaAElIASUAJKQAlcbgQs7wEurVwHXDLXwfTp0zG8ZjhWrVqF1atX\nGwGBxmrLS+Fyu9e3Vl+7eCB4jb3eClFgLd9aOTw6Ljc43E64PMyrEN9yWjlMVi3sOVnXMgKCpSL0\nO8EmIYuckkOBosFl6/zR7350VQkoASWgBJTApUhAhYNL8alonZSAElACSkAJKAEloASUgBJQAkrg\nXSNA4YCeBBQNODNRcmZmJgoKCzBnzhxs3LgRO3bsMF4J71qlLuKFLB7xhMLxitB+fwYb/nnUMn5m\nvEyWeOZyuN/M/fafTRSw6kdPg7Mdcx4V00OUgBJQAkpACSiBcxBQ4eAccHSXElACSkAJKAEloASU\ngBJQAkpACQwOAjRGUzRwuVxm5jrzGsyePRsrVqwwXgfHjx+XED4h43UwOKjoXSoBJaAElIASUAKD\nlYAKB4P1yet9KwEloASUgBJQAkpACSgBJaAElIAh0DfavVc8cLvdRkQoLCjE5MmTkZ2djaNHj+KV\nV15BY0OjGRlv5UdQhEpACSgBJaAElIASGIgEVDgYiE9V70kJKAEloASUgBJQAkpACSgBJaAE3hoB\nEQ0srwOnBM/nnJKagqKiItTW1hovAyZMrq+vNyGLmFBZxYO3hliPVgJKQAkoASWgBC4fAiocXD7P\nSmuqBJSAElACSkAJKAEloASUgBJQAheIgIm93088YMgi5j2g98G0adNQWlqKe+65BwcPHkRnZyci\nkQgoHnDWSQkoASVwSRCIxfoSuFuJ3PsvL04drXTnF+fqfdnWL9Ll9bJK4HIm4LycK691VwJKQAko\nASWgBJSAElACSkAJKAEl8E4RsEIWUTCgxwHFA6/Xi+rqarS0tJicB1u3bkVqaqoRE3gMBQTrvHeq\nHlqOElACSuBtEaD42e/EiOiajos2ZDiKcNCPo3v2IupLhSe7EFk+G5z2/jXsV9kLtfouX+5C3YaW\nqwQuBgEVDi4Gdb2mElACSkAJKAEloASUgBJQAkpACVySBCwRgMmRKQxQOMjLyzMeB8x3sGHDBjBJ\ncn5+PjweD8LhMEpKSuDz+S7J+9FKKQElMBgIcFR/FP7uLnR1dqCjoxP+YBShiB0erwNeXwISk9OR\nnOCG2+m44EDE8UEEVSDY04EdL/4VoaKRyJyUixSXhIFz/32W/Fg0IoJtGNGY3Ae9wpxnU0ZixiMs\nFAjBJu9yh8zULP6+q7/D6GIS8i4aRjBMXna43M5Lq37v8O1qcZcfARUOLr9npjVWAkpACSgBJaAE\nlIASUAJKQAkogQtIgOIBvQ4s8SAUChlvg+uuuw6PPfaYmRsaGhAMBo2wcPfdd6OsrMyECOG5OikB\nJaAE3l0CYnlGB/ZuWIa/Pv5H3PPIw9i5/0SIoAU3fgwLb74TN8yuQUV+soneY+PP+P/eqtJbgRZ/\nfjzDe8xSA2Qvwx+d+13Ha8cQPN6KHT/6Mnre/xMUV0xBdVoCEkQ4iBd1hmtYFTLv0d76yXr8SJZp\ng7+rDZ0t9WiNZcKTkILiLJ+8r08py1wgiO7OdhzYcQQJuUVIyclCijt2wuNBjmGJRuEwx7P0U8rh\nXXBf72T29x3CsFDWnn7Lvvr2bjNl995B7wnxPxM2RIJdCHa3oK4hBrsrARXlWVI/+0m1MKxNUcJN\nium7fL9L6qoSuFAEVDi4UGS1XCWgBJSAElACSkAJKAEloASUgBK47AhYxjAuKRwwXFFPT4+Zm5qa\n0Nrair179xqjGRMl09ugsbER2dnZxgOB51hlXHY3rxVWAkrg8iLQa5TubqvH4a1/wSsvb8Pzrwcx\n5+Zv4f0ZiTLCP4LmgxtwsKERTz36ADJTPgC/fRSqszxwOeJW6BOGaOZrsRtj+olt/XDQ2t17vfN9\nx8UQQU8QCNujsDvcMuqf3gHnMoDH6yTD8OUwqUvvR1OLuG6AnpZ9OLThcawPLUJawTAUZiVIrU+e\nKAnYREg5dGAr7rvvUdQufC9GTp6J2hygzxDaZ+CPX+vkEk586n+vvVXo3SkywhlBnTjXrJ2RW1xx\niAab0dGwHi/8Vf7eJBfgQ8XZSHaffD6vb133fC538tn6SQn8fQT6vi9/XzF6thJQAkpACSgBJaAE\nlIASUAJKQAkogYFBgIYazvQ64Mypra0Na9aswbFjx8w+igiBQADt7e04evQoCgoKkJOTY8SGv4dC\n/9Gt/cvhdmu2EjLHB6+eGPlr1duqe//zrXXu00kJKIGBQcAyKB9vOow1j38Cy16bjXWhSfj0je/H\nyKocZLpDOLLleby0dDnu/8Z/onjEGESSi1GWLu+qaBD+HhnxHnOZXC2xUI+sSzgfpxtpKSlwiZHf\n5EeQF00o5EfQ3y0CagghsbPbJeSQz5toPK4oQJz1veIUg/hwIOIKIxToRPOxCAIuCWEUdSAlORle\njxtOns+QPTIH/FIfea92d4cQsTO8kBsJCT543C4jdNhiYbQe3YWtK36A53uyUViThPElbuRmJcLl\nkYT2vY+VZUWPH8G+bSvxk3t+gVtSqxDJqkC2Iw25aSKaSL0CnV1yPT8CsYhc2yHvbreEc0qG2yVh\n6iiqiOgRlhhC3ccDcr8SGknM9x09MSQnJSAp0SthmLpMqLqAALHe21z6EpOEiw8Om4RUCgXkGqdz\n88h9M8RSV/sR7N2xFH9+zA1PwXDMuqIQpYWZ8DnlXmIhYU7RWupI5k6PlJuIRK+Ee7p4iSsGxhdH\n7+K8CahwcN6o9EAloASUgBJQAkpACSgBJaAElIASGCwE+hvh3W63GM5C2LJli8QO7zBiAr0QmN+A\nhqL169cjRQxtGRkZJi8CGZ3VkPY3AJ7tPF6P3g68fldXl6kPQyXx+vSKcEn8brfkXEhKSjJ1yczM\n7BM9/sYldbcSUAKXLQGxKKMFzfX7seQnQMZnr8I/X3kdJg4rFu8CLxxi7i4bsxizkISf3vlbrDpw\nEKuWbsL14ydj/4YlWPnkw9iCCrS0daKr+SjCMh4/K7cAiz/yRUwcUoD8VCne1oF9G17Ci4/djw31\nLhxpE6N8uBszr70NU2fNw8SKZPg8TvMuir+/4qPpiZRj5T1ZRdgh5y9vacYTjQdFJGAQoxjm3fwJ\nTJg8DaMKvPL+CiDYeQhLH/sfrN9yEGv2BhCO2pGUno3SMddg0dxxmDAsDQeW/QZ/fX4JfvGAeA5k\nPohd61/H6gfzcPtXPoi5iyYhyx6D2yFJmQPHsOKRh7BEwjYhpQAbnnsA9VtW4omsefjge4bgyrEu\nLPntE3ht9VbUi+AQESEjM6cA06//JKaNKsWwIq/oBoew840dePQXy+AraRbBI4AVq8K44WM3Y+7C\nCdj1zH3Yum0vXt/RLjkUPOJx5kakuwkTr70Tk2bOweTiAPZvfAXPP/p7bKx3x7mFOjHz+o9j0pQp\nGJuyDcuWLcPXv/MrONwjEG57A5+/7ddY+NGvY+qM6agIrsHrS1fi6b++iS4KMGkifNRchdveMw5j\nqrINR9WB+Vum04UkoMLBhaSrZSsBJaAElIASUAJKQAkoASWgBJTAZU2AhjB6HVAYYHLktWvXgvkN\nLAM/l5s2bUJxcTHGjRsHigw83tp/vjdPAYBCBBMvUxzo7JTkpjIaloIBRQt6NjQ3S1iL3n0UDbid\n3gcUDnhdJmtOlhGzrCuFA58kRPV6OUrVK6N2ZZSsiAppaWnmOCZ+1kkJKIHLnABt9LFueVd0YYWs\nvr+8BKPHV4toIGHWZNQ8R9J7EjIkmXsRaodMwRuvdWPv7iYxyofQduwQtv74Efyu4ko0+1JxQ40X\n3YeeRcfRQjxbcjXyUpKQk+hGy97l2LbxdTz/yh74KsfIu0VyFzRtweqVG9ERykJZ9iQUinDg6LNi\n0wOhl6ssHTICv/NIPZ455sPV+YlwBo+hdfMLWF40EyFnEYbkVCHYtg+zux1xAABAAElEQVQHty3F\ni8+vwsbdUSRUV8AbaUJ34zY8/GAEOZLHID1jrLxb3ZLo2SdCg5QvPxxirE9JSJL3X//Ex7y4HU6X\nHCveAzh+TD4ViKgrxyb74IwFEe7uRPvxHvEg8CAjPwPdx7ahZX8jHnl6LTLFm6CisBTuaBfam/bh\nz//v+8ifNgZueceHkSXiwFG0HtmCl5Zswo7dbfBWFyB2bAv2bD6MlVuPoHjGRxGJ+XF056vC7TU8\nv2wvEqp6uTVuxBrh1trpRfEiD2LuRCR7s3E85BQPCxc89FbwOUREacG2pc9iyxt1WN+SiDGVkuQ6\nySteGyHJgW0JM1xaoHt560IJvMMEtKXwDgPV4pSAElACSkAJKAEloASUgBJQAkpgYBCg8d8SACgM\n3HjjjcZwT/GAhvmWlhYzypYhjEaNGmWSJfvEqGWdczYKFAn6T/xMIYCiAEUIztu2bcPOnTvx8ssv\n9z/0La+z3hMmTEBNTQ2GDBmCSZMmITc314gLzMdw0sT7PWmDflACSuDSJyDvE7sHnVLR3ExJFpwj\npj4bPRH4bY4bl+1OB5IySo0x3UbDsyQPMGGApsk5rcNww6Lp+PTHp6B9QzV2rF+HT311JeaPlZH3\nhSlY+8RdWHtgFnaP+Bx+ftdcjCm1oXPPUvz+4U34l88+iIULRyBVQgWliIjJSzK7AC9rorxJ7CC7\nJyIj8ktQkzoVn/va9ciI1WHvSwE8vPIQ/ty4FjfNK0f7ztV49f678OOH7sLNt0/DP319LrKxEwe3\nvIkvXv8lrFxeDFteNT4w8RbM9aXB2fkwXordjIKhU3DnoirkZqdCIvj0hioS0cCdjolXXQu/w4nv\nP/UvmLLgZkxaeB3m1xQg09WCcGcdhl79IYy4KRNjRmajY+8L2LRmA66+fQlmj8rFlBllIhGIAOwM\nIUUoOisXo3TCVNwyuxLpsW04tncJ/rSqCtPmj8ZX/3ke7HVPYsWS1Vj5L3bUVg7B0NwI1v/yH7F6\n/yzsqT0Dty89jmtv+BFGz8zCv3+rGT/8H/Eay63GN781DxVlKTi+Zwf+8MWfo/u2b+GWz9+CD8xM\nh0+8KQ4c6kFZToLUSKY+dSb+UX8qgQtBQIWDC0FVy1QCSkAJKAEloASUgBJQAkpACSiBAUGAIgA9\nCBgGiAmQZ86caUbwP/XUU+b+OOK/rq4OTJRML4HExEST54BiwNkEBGs7PQj2799vRIJDhw6ZJMv0\nZuBMUYJCQn5+vvFEsLwPWC5negzYJXmozW4zXgdW2CRWih4IFDC45LRjxw5T5saNG/Haa68hKyvL\nlFtVVWXEhPLy8rPW1RSgP5SAEriECVAccOAYiiQngUvi39N+f7IEyHeOw+EyWyORmAQwkjwDfonh\nXw9cc+d8jBw/DpWF2eK5MAyRLslmLOVFwj0y21C/X8pubEUk6RDWr1olRv5udBx5FdtF2IQkID56\nrA7B5l1oXb8WPT6J/W/zwd+dhElXjEJ2ihOdh3ehaMR7UHPlNRhWXoa0cAS+kdPhW52Igy0RERl6\n0N7SjfqtwD9+5wqMGjce1YVZSHT4ZNS/DR/+BFCXHELdoXaEJ+TCl5CKnMx8pIm3Q1palrzPUiXu\nv7tXIonft03ejd7UDKRm5GCs1DIzLRPZEoIpM92HFHceQjKyf5i9Tby4WrBlzT601tdh56FWOXI/\n/MEeEEGGcIzCJ4GgcnD19EkYN3cKhuQnINpwBO0xyX8T9IgQk4yMzDSEG4Sv5ESAyB0uyW3gDB9H\nQ539dG5HyW2HHNeJA02dyM5zIT8nU/6myHvbly4CiNyTeIlFkxNQfsdELNv3Clb9qQtFrmtQM6QS\npRUFkl/B0yuQSDE6KYELTECFgwsMWItXAkpACSiBt0+AneIzTVZn+0z7dJsSUAJKQAkoASWgBN5J\nAmx3UDhgDgGG+qGxnUmR6RVAo781MWkyEyanpqYag73VXuGyf5uGAgBzFDAk0Z49e7Bhw3q89NLL\neO6556yizJKhhRhWiCGIKAJwnfVg2CHO3G6FG6J4QY8F1ovlU0SIRCJGUOCSQsTWrWKV6zeVlpZi\n8eLFmDZtmgmHlJ6ebkQP3iM9EVhn6x76naarSkAJXJIEosjEIfhDkszXL7b4BPajTogHEXkn9HS2\niiG8BG6f0wxWj4REQKgDKoaVooQGabcNHjG2p6TnyrkhxKLyDomIJ1RjvYTIkVH9ORJ+p24P/Afb\nJHlxPbolz8HEqQkSosiPlqZ6bHvtRbTJe6RTatLcmIWSUeVIldBAgQYgfUIOymsqkJLoQ1IwAelZ\n+fL+krp2ST0l4bFfki53Sqylqi+XonxYPpKlLg57CpLTCsRgXor2LhFA2/ySi4AJ6yU5sFNCHsXE\ncC9iiFO8Csy9nnzLVFDF88AFjs/3SNgit8tj3m02MezzHdnaVIcD++pwuLFT3p3NaOiUMEBoNGGc\ngtQA6JBl84g0UoWiojxUlmciWbb1uLySuNguAkY7Wo7tw9aNGxDYdRhHW1mPAiT65DqRgHBrFm7B\nM3KbNjNVhF85XN6zLgmz5PTY5J4ckjBZkjSLLOBLSkXFzFnYFl6FP/zup6hJSUZ3exD2qePgLHDK\n3yNHv6cr5eikBC4QARUOLhBYLVYJKAEloATOn8DZOqZvtbN6tnLOvyZ6pBJQAkpACSgBJaAE4gSs\ndgiN9TTQ01BPgz29DoYOHYoFCxZgxYoVWL58uTmBosG6detMCCPmGDh1Ynk0VtE74Y033jBCwYED\nB0BPA16DXgAUH6yJYYXKy8tRUFCAvLy8vnJZB8uTwKqjJUxYAkJ3d7fxWGCdWObevXvNzGtzojBA\nQeHpp5/Gq6++akSJefPmYYok7Jw6daoRSMyB+kMJKIHLgkA02i1pjYGjTc040BCQcDdxbyOr8j1d\nHTiw/c/iDTACCRkJcIrVWqIIiUVdRtVH4iKB+DFJDH/JtRKjPwKt8HJEzIloux9pBcUYVTMBkyQR\ncl6SDf7AbExfIAZvbwKGD69EV1MaMm76EAJOO0Ji0A/3JIrXQCYSbF0Q276ImOH4dcRQztJ5DSZI\nltdi32STG+A2GtNPTCIgxLJMPQJiKjf7ZWdMPArM1P/8futmn7zjwuLd0CYfIqZMuZ68a7ub92DX\nuifxH795FruaE7BY6j20MhlJktMBcJ9SbEwoMBl0FIIJkjJCqicpp6Vcj/N5/On+zVjypIglx7Nx\n5eJb8LM/zsLw2nw4wofEGaMTaXln4ib5J7zJ8nckH4nBDrTJs5CP8Mhsk/LJJyE1HxNv/GfkjtqA\nyZOW4oUfPYjnlqzEg+P/Af/nqwsxbUwJXHJP1t8AU2n9oQQuAAEVDi4AVC1SCSgBJaAE3hoBq8HD\nUXLs3NItnyPxmAyQo+fYCbZEAXZ0rY67NRKPI/DYibbKeWtX16OVgBJQAkpACSgBJXB2AmxfWMIB\n2x40/rNtwrwBXGe7Zd++fcZQTy8EbmdeAU7WyH22aXjMli1bTFii9evXm9wFTHjMdk1OTg6qq6sx\nY8YME0KIIgKTHHP0v5XsmCGQ2N5hXViuNbF+lnDAJQUBtp+Yx4D1YJuqtrbWhFFiXY8ePWpCIlG0\nYHilw4cPm3N4HtdZzxEjRqCyshIZGRmmfta1dKkElMAlRoCWd1uavCfS8J4a4MDaTXjeUYzS941B\nUXYCPLagJPLdhc0b1+MvMqI/cU4Bhk+qlHwAMrJdch04xE4eN973N9b33qMYyO1OF9JKgcPBmIzM\njyJtUrGMvM+ALRwUL4GAeABImZ5U+LLFk2BMCiJSnaicF4s4kJ6dLEmPO+ASGz+DH3GybPti8o5v\noE4ggoXX50LiJGDL2m0ymj4ZY4uHICHciOYju/HqyjU4Vv4eDKulN5eIG+IJEQ7sFO+qHqmDX953\nAbkfSTQsY/UdvXqCKV48DDwyV/C64jnRE2Df0olQcz2O7V6OY225yK+cjOmTxyHZvxX7jh2WIxNl\nPvF+jVdSfkpOCE78GZDEyp2tR+HNKEbNlFKMrsoScSQfNSPHYNLoHGSlJcJ+nNwKcDBwKreQqXNE\nQjAli+eHXcBERJQISZnhznZ0dgdkexS2UBBt7VGkSOLoiQtS4OhswmvrmvFvD+1GyydmICD1oEHX\n4imrOimBC0JAhYMLglULVQJKQAkogbMRYIfWmtnZZic1FAoZ13q67LOz2tjYaAQEigiMFczOL8+x\nRAN2oCkWMClhUVGRGYnHsADszPMYdqg5c/SeNamoYJHQpRJQAkpACSgBJfBWCLANwfYFR/nTcG8J\nBwz1w7aL1V6hgX7z5s1mG49hW4TtFw6MOHLkiBnZ/8Mf/tC0dXj9wsJCUDiwjPxMrkxPBstgz3aM\n1X6x2jT8bG3rv97/flhX1tPj8YDhh1gHmua4YJuL4ZXoecBjWH/mUqBXA3Mf0IOC05e+9CUsWrTI\nJFSmhwXv5WzXMyfoj0uCQPxZx6vCdc4UuazZqiQ/63Q6Aet7xj1ct+ZTf/et7+DpJVyMLTQdpyMt\nPQcT5gHPvLEeD2xxYMLoFDFQpyLN0YO9q1/CG2+uwYNrgK99rBBjRpeKoT3uceDKlHvle6Wv6rJm\nRvNzixjineJlVT0Grl3d2LD1CDqvHCZeCQ74HFEERBDt9ouYEHaKcJGIjJT0vlL4u2eTBM1t7RKK\nR7waIjKqPi5QxA8hQ7tDQiNRVYCIBsleZIiF/7kVb8oIfwcmDk9CUtcOSY68Bo8/Bkz6ohuTi9Pl\neJtkEhAvAKleqLMZzZJv4NAhDwryc5AgQqvdXJd15+yFz5OASl7yeKsIpYdQn1oIUQwQ6NiG5PQP\nIr94BErz0tG+S/IaSM4ZQMqw9xMOpJ4SGO6kuvt7OtHRdgCulBpUluaI4FshIZnE4yIzC85gs+SO\nkBwEDi+yqgrg2tlzCjd/nFtPBGlFUcmHIPdPN4ZQK9qbDmDf/gMSeildcjuEsHPjdqQWFiE9Lx/V\nU4ajMSbCxkPd8h4X4URqyje7TkrgQhNQ4eBCE9bylYASUAJK4CQCVkObgsCbb75pOs+7d+82HWp2\nuPuPrmNnl+IAG+3ssHJih5fHMVYvRYbnn3/eiAsUDujGX1JSgjFjxphEfxytp5MSUAJKQAkoASWg\nBN4uAbZbaACz2iJcZ74BWuFpfKWhnwMXaIDfKYlCly1bZsQACgc03HMEPxMS/+UvfzE5BlgOPQfY\nlmHZt99+uzHOsw3DNhDL5kwvBAoA1szzuM4lZ6s9xaW1bhmJueTMwRmcWU9L7HDIcFx6IVAMGD58\nOK6++mrTnmK4IgoYFEE4KIPhl3bt2oXp06cbLwiGMOJ1WK51vbfLVM+7cAT6PxvmumCoKg7IYRJu\nazAOfyc48VnqdIKAxY7fM37/6O3Dfgi9gfh9Md/7E4dfMmvytTRTetFQzLvradirXkTrr36On/9g\nvYxctyPBHkNT3VE4Mkfh899/GNfPmoCaYp+EKvJL/H0/enbJCHrJixC2fh0k30AkJEkSJMeBX5In\nexLTMenG7yLw1xew/LOfxy+PXyVhdcSTAT3oiRQjq3gcvvjPpaiWhL1nej/E5P0TqAP84+V6kpTZ\nXEbCFEUjfrS3hbHmYMjkLSgdOQVz7/gFNn//Xqz+3VLs2fAYnD0N4lkQRtp7v4cZV1yJOSNkoBg9\nJDJzkTv8y2j89TP47cN/waoHc/GJb3wK86+eLmmMJdiQsfsTjHhiZBdjwmfH4/k1D+NXry7HX2re\ni/fOTMLkaV9F4dLH8cDdz2DvujIJtbQTTSLwQgIbBQJ3wsaKSj0jMvJ/E9YiKKGJLLnNk5CExJQS\ntOw+hJCvFQfLgfpAO1pbOrFj337c8NEvYer0qRh93d0IvLgEr3zmDNyKxuKL36hApfxuZRYPx8jM\nl/Hgb/8LX9n3CG68658wYlgFDj/979jW6MTecCJszU/A774Ot37zDiNWpEr1eh+9rOmkBC4cARUO\nLhxbLVkJKAEloAT6EWAnhfF2OeLuWLMkD2xsMh1SdlA52o6da8YD5ug7usVTCKBw4PF4paMcFw7Y\nGA0FJXFWl4zyEFd7doAoINDlnh1iy2OBI/vYUbdiArOxz069JT70q5auKgElcAkS0JGQb/2h0OBh\nGT3e+tl6hhJQAuciwO8W2yA02LMtwTYLP0fEIMZ93E4DO9sx9DigkfbgwYPGYM/PS5cuxb333msu\nwfBBTK5cVlZmBjswJBDX6UlJjwarPF6HBkwurXVLOLCO4bL/xDpx5jvUWlriAQdecD0UDpm2lam/\nfKZgYSVzrqioAAdzsF3FHAycGMqIBmgez3qzTcXp1GubjfrjohHgM+czpvcI29YUpigasN3NtjLX\n2U6mOMTj+Pz4THU6QcBiwu8hhQN+n/n7zu8s+xRcp+jHgUnsq/A4fvcv/hR/D3gSM5BbNRlj2iUJ\nctCGdXslnE6XeG1LIuGM7FqUVtdi6tzpqC7JRqqXlnU3ssuGYsK/3oW04izkJkqyXfm9cCYUIrvE\nhk/+YxTF+SkyIt6LzLLxGDY2gFu/2oHdnTY0doTk3kVYSSpGflkefC6m8z3TZIM7IRXDP/45hEqH\nITPdI0Z9aa+4JAxbVi3mLIiidmqKOT8pqQglI2Zj3rX1KBp5FHtb6ZmegeSMXAkHNB+jh1cgLzFu\nwvSm5iF/6HxceYUPuUUt6O5MRZJPcr9IJU5+LUo4oMxCjLrmThwv3Av3HgkNly/1LioTVuWYvrAN\nnvztOCIj/rOyZmDI2ERM6MnC2KFFSJHkzHZHKrIKK/GdT3wT5UVZSBJsdhnr39l4HI3b6sVjYDjy\nqwoxekSJeBpIAvo1a/ALEVhGzP4AKsa5RKAZh5qxQdz6lQ7s6TqFW2k+fJIPwuVKgiuzClOuvAKu\ntHxsOdqBjKRkpCYmwz5sFDoSOiTJchT21NtQUFmL8VfUoignxfCOnXyzZ3oAuk0J/N0EbPLHQv9a\n/N0YtQAloASUgBI4EwHrTww7MzTyHzxwEA//8WGTDHCNNKze9773Ydy4ccZDgHF9OaqHDXVrJN3Z\nO6XsGMdHSsVkJEhIRsmwk0QPBCYlfOmll0yyP7r633nnnZg7dy7YGWan3KrT2cs+053oNiWgBN4t\nAjRo0Eil39HzJ873Gg0YNGYqt/PnpkcqgbdKwGpD8D1lvavYvuHMHAZsg/z0pz/FBz/4QWNs3LZt\nG1atWmXC/3CUPwUFDqK46667TPunTAQDfm+tEc6WwZJLa+Y+a2b7yJrP9l1nHS3xlUvOFAw4wIKz\nVXcuaUS2DMk8hm2pPXv24JFHHjHCAQ2lHNxBoykHc3znO98BEyhb9TlbHd4qVz3+7RGwfh95Nv9u\ntra24vXXX8czzzyDF198EcxhcepkCVH9zz31mMH8mb/T1nflVA70amafYvHixSaBOL8TDPdlTRf9\n+yDfffOP8f/lu87Y/yFxI2AsfU+CBNuR3AAuyWtgNyGDxHgvFWdS5Kgca3PFc8Ux/A9H2UelLBmH\nJe8hiqUUmUSMNO8RaaNJnoCwJDaw2Tyy3w23R95XYgA/6/1LWeGgeDBI+B+bUzypjM7Bjpx4IjDZ\nsKx6PLKP9ZdtERE3QzLK3y/nxGIcQOaGL8ElS3n/yfMxtnJzbAQBv4TtkXsMi7iR4JV2kAl7ZD2R\n+NLUXZgEmAtBQvw4xFvAI/V1iidGRHIjBPxyLclD4PaKWCtCLVMhk5VTxBC5c2Ekfc2ghJ5zi1Dk\nYGaGTiz/xb148jNfQc93H8e4qWPw3kk58LnbsGHpS/jxwg+j6vv3YeQ178WiKhGgJExTUAa+nZkb\nxRrTqZX7Zq4GeW6S88ArXmcej9QlHEBQIAWlrxu1u6VOTgm9RMFKRA0D4uR71U9K4EIQUOHgQlDV\nMpWAElACg5yANH9MK5ANSI584mi71atXmw4MO5uMCVxeXm6S/9GYz5FunCkavN2JXgbsuLPTxGvS\nLZtCAkf8cfuQIUMwduxYTJ48WY1rbxeynqcELiABfodXrlyJHTt2GG+ks3ZAL2AdLseiyYkGwMKi\nQsyaOcu86/g+1UkJKIELR4BGdhrkaXSnYEAxgIZbtj0Y3oehiQ4dOmS8Hzlin+0Stn8WX7NYYotL\nwlIJBcRRyxzRzLaPJRJQROBnHmsZePsLBfy+8zOns70jLYMwlzSYRaNcxsUE1psz3xk0LFrCgSUe\n8F7a2tqMlwFFj1deecXcB89hHSkaMGTRtddea4QR1uVs9bhw9LVkEuAztdjz923NmrWSeHuzyV9B\nrxE+R3odcObvp05vnwC9lulpwJn9FnrelJSWoHaEjP4ePx7MTcKp/zN5+1d7Z8+UXxOpF/M1vJPl\nmp6elNtrxH8niz6pLAYGekcrLuWx7ka5OOlK8qqMp3U4aeuZPrBOUexd8SzeePLX+M32THjS0jGy\nMAEuySXRWt+GNctiuOMHd+CK+TNQlBgzIkW8pPPjxuelmsCZ2Ou2i0VAQxVdLPJ6XSWgBJTAQCYg\nLR52SmnE37t3rzEGMtkeO9ULFizAxIkTMXLkSNMAtzo9Fg42ujmdut3a339pHctt7GxzptcCJ4oF\n7JSzM8xr002b64wfzFF/Vmf9fK5jCtQfSkAJXBACVkebRqy1a9diyZIX8eyzz5hrcZRrRLZrD+p0\n9ORGwyINfXzXzpgxA+nSec3PzzdCrMX19DN1ixJQAn8vAct4T2O6NaqfS7Yx2A6hgPDoo4+ayzBO\nen5BPqoqq4xoQE9LK4cBz7faLxQMLBGh/4j+/sZ5q81ilmZk8NnvJN5GchhjJtetmfXkdSkG8Hps\nG7F9RvGW1+I+tp9YLxqd+Z7hABCe/7vf/c7kaaDwwXxSDOHCulr1OnttdM87ScB6lnw+/F1jO/ex\nxx4zXga8Dtu4NHDz95Gj4vlMLSGK+/m8rN9hftbpBAF+P8iXk+V5YAlt/Mx+zfr1681+eh/wu8Pv\nOPMgUGDgdEl8H3gP8pxpgOZs3dMZ69Z7rKl8vx+nb+Z75MT9caQ8P8sWc41+p56+ak6MH9t/Z/z8\neB37tstGFmszCZrNBeSzXKPvgBMrZq/8oGfAuSvBI3mUlBNfjRci6+aj6BMWI7OD7E5cxuyLs6OQ\nYUd2ZQWGzVuA1K2P4/n778ezvcdOmPNeDL3pBpRXlKA4VcI+sXC5grl9PgiZzsWNdYgf1nt1c6I5\nixXkLbAE/tBJCbxrBNTj4F1DrRdSAkpACQwOAlaDm4YsdjA3bdqEvTLy/2O33Ybx48ajoLDACAbs\nkFqNV2v5ThBiU5NNPdaDnWCOsmJcVyYlZMeK9frkJz+JSZMmGQMbO1M6KQElcPEIxDtJ4vgtYt8P\nf/hDExajpqbGCIwUDvhd1unMBGj44Tvu6aefNsYjGoZuvfVWDBs2rF8n98zn6lYloAT+PgJ8d9H4\nbo3cp3Fxw4YNuO+++8ySYWIYU57vM4oFV111lfE0oHHR4/XA5/WZMCdsD9GAbxl2+b22ZtaQbaS4\nrejtGYssY1j/Jd+rnPvXv7+AwPYTjdIMU8TR7Gw/8T1DQYFiAev8+c9/Htdff70xlqp48Pf9Lr2V\ns/kcrWdHA/ZvfvMb84yY24vPhaGmOHH9lltuQW1trfFE499Ty7tXRYNzEydffh/4+88cEUx6TvHs\n4YcfNn0Lns1wqPyeMDcbPQ7uuOMOI6bxu0C+72Tf5ty11b0Xg0DUhBDqFm+yNhnAEZDwQjLIRXJG\neHyJSEpNRnKSz4ROYt3e3pv7YtyVXlMJnJmAehycmYtuVQJKQAkogbdBgJ0ZNpTZuGZMX4Yc4ci7\n+fPnGyNgaUmpxGw8EQv0bVzib55ijQ9ho50j+jizo3TllVeaRGbMrWB5INx0002mfuys66QElMDF\nJcD3Bzvh7HTTOEXPIBqodDo3ARor+Z6lgbKzo1OFlnPj0r1K4B0jYAz60uZxScxpfg9pYGe4NcaY\nZ2giTqNHjzbeQAyVyDCNHAnOAQtsmzA2Oo27bINwW3+DY3+jY//1t1P5U8/nZ7aR+M7lNS3BgnXg\n3F/EYP1oeOZ2HscwTJxpVF0qCZ9ZDttXNEpbbcC3U0c95/wIWIw5yp35vNjWZi4DigaWCMQwUvTq\npWBFzxDmqeDfVP7u8fdOp/MnQI8+5jVgaCJ6S7M/wxBeHBT15z//2XwnODiJMz0O6N08Z84cM0DK\nelbnfzU98nIiYHd64JW5IDFdqh1FWHIn2GzMgUCx93K6E62rEvjbBNRS8rcZ6RFKQAkoASVwHgTY\nQGbHmZ1lGubvuece08CeNm0arpEkYm7pfPIYzhx6YRn4/z977wGf1XHm+//UK6ghEIgi0XsxGLAN\nLrjGjmOn2cnG16l3N8k/m2yyyd3s3bRb8tnkbjbZu3d3U27uJnESx3ESbxxXXHHDGNs003svAiEQ\nqLf/fOfVA4cXCSQhgSRm4GjOmTP1d857Zp46Haj6grLQHoQxxDuELYzIhx56yG/8BxE/ZcoUry0E\nQQwBHEJAICBw6RCAocVvFg1evicENP/iGV+Xroe9p2Vw4psFTjCMPE5+V8Pe08fQk4BAf0eAb1Nd\nXb1f+zz55JN68cUXvY95fKGXlJTo+uuv15w5c7zGN0x4U2iICg1Yo3BQl33rLO5O/Nqqk3b5jnBw\nbsID1kTWJ5jP9Je+M65169Z5hvSzzz6rpUuXeoYpLnG4b2W6s9+hrtMI8N1HSLxz50795Cc/OWUF\ngvAYN3Vov999991+H4rS0tIzNu6lLEcIHUfA3ntTYkBgw/5pCAj5PSGwOXDggH8m3/72t/3eH9AW\nHPwm2vrNdbz1kLPXI8BvyncywW+qHHN6FPMo5B5+sDTo9Q8wdLCjCATBQUeRCvkCAgGBgEBAoF0E\nIERYHONq5He/+53boO1tv2j+8Ic/7InlFGeCT7gUC+hom/n5+Z6Yop+vvPKKX+B/73vf04c+9CGv\njYWWXTR/uwMONwICAYEeRYDfof0Wo+c92mgfrdxw6qPdD90OCPRZBGztwybIWBmgNIHrGIR4aCjj\nnui6667zCgvGdMdNEcxI0+o3pv2l+M6d/nY4pldS7Jtr/UEAgPCAfuIODcY0ihaUQVD5xz/+0d+D\nkcpeDsRsnEw5w6XPPthe2nFw5fmwF9ADDzwgXGGxf8GJEye8Ze2tt97qXROhJAPTmmcXDaefdzQ1\nnHcGAYR/o0eP9lYc/L5xXfTjH//Yu/XiWezatUs/+MEPdP/993tLnPBb6Ay6fTBvEA70wYcWutwV\nBILgoCuohTIBgYBAQCAgcAoBFsUcEM5r31nrCWfMotkEGf+fEC/c7w0Bgha3RVgfEHCltHXrVi9E\nQCuQfkOUBeKqNzyt0IeAQEAgIBAQCAj0TgRY18BAh2GO6x7cxrBJLUIBmOxXXXWVX2sUFRV5FzGk\nIzRAgADzkfWIMekv9Qgd78uFmPsi1j+2DuI8uh4iHaYpYz548KDXvC4vL/dCE5jVkydP9lrvjBF8\nomUv9Rj7Q/u48gN33IE++uijfkNeLER4Ju973/u8le/48ePPsDLoD+PuTWPgneb3y8GGyAhr+F08\n8sgj4rfAPmo8G4QKWHzw++e3H0JAICAQEOjLCATBQV9+eqHvAYGAQEDgEiMAYWgbiGG2i9n0c889\n52M26OR+byMe6Q+agGgG4Vbp1VdfFebFmBVD7EIIGNF8ieENzQcEAgIBgYBAQCAg0EsRwM8/rkrw\nM/+LX/zC+0LHzznrCfyhszcAWt9RawOzNDCmfG9irlufWCdhbcA166HomggBAUIPxs36j41j8feO\nKxeY1ghM8AlvoTeNz/rUl2JbR9NnXBQhoFri9paAQc0zYu8C9jJ473vfq9mzZ/fKdXdfwrujfeW5\nIDzAogi6YePGjVq/fr2OHDninw3PKCszS+++892nLD/s99XRNkK+gEBAICDQWxAIzpx7y5MI/QgI\nBAQCAn0MARbNhBOOkEH7iQUz2ja/+c1vvNYT93rjItmIWCwh7nB7L9x4442e6ELggZsBNAjJY+Nj\nHCEEBAICAYGAQEAgIBAQAAHWB6wTjh8/7jWNERwQcB0zbtw47/4Q4QGMRdYaMBYRHiA0gOluayNb\nj/jCvegP/UJYAGMajXbGgbUE+xswDhQv2BCZPazYYwXmNdYWv/71r7Vt27awhuqBZ8k7x/vGRsis\nt3G9yYa8bLr9pS990Vsd0Ky9Wz3QhVBlBIEozlh8fOGv/so/C54Jz4Zn9PwLz/tnFuiJCHDhNCAQ\nEOiTCASLgz752EKnAwIBgYDApUWARbARzuVOax9rA7RsFi5c6IlJNM/s/qXtafutQ8CjOQfRhRYX\n2kEQymhsQRQnO2LZW++3X0W4ExAICAQEAgIBgYDAZYQAaxs07auqTmrPnj1avHixli9f7l304JaE\nfQDQAId5CJPd9jSA+Q4jnnUGobcKDexRWv8QdFiwtR/jZw01ceJE3XXXXd7lIxrwa9as0bve9S5v\necA60MZq5UPcNQTAG3x37trp3UKxOS9WHeDPmnXGjJleONW12kOpC0UgNzdXs2bO9M9ip9u0Gtet\nWCDgWorr3Jxc5eXneaHhhbYVygcEAgIBgUuBQLA4uBSohzYDAgGBgEA/QABChuPAgQP6/Oc/rxEj\nRui+++7z2nUMz4jOcw81JoAwYrS9nRBO3XcEe3cG6oXwuvPOO/3mf+x3wMHmyU7y4YUf3dleqCsg\nEBAICAQEAgIBgb6JAGsGApaJW7du8wIDGIMwCDkWLFjg9zUwCwMTGph7ImOkd2x9FMUobq3Uuj6J\nro06dt7M0kYdXUnRT/rMgdDD9mlgXFgiYFVx2223CfdMCFEIr7zyinenU1NT49dQhll0NOG8Ywj4\nZ+qeVmNjo7fsfe3VmFUspXkHEdLMnTs3+NDvGJw9lovfCb8NngXPhGdDIMaSee26tf4Zul9xoCt6\n7CmEigMCAYGeRCBYHPQkuqHugEBAICDQDxEwIpAF8a5du7R9+3ZNmzZNJSUl3kQfArnjgY33zp+7\n80T2+ev0OVzbEL9YGOCn9NChQ1q6dKnf2DDPaRCFEBAICAQEAgIBgYBAQCCKAOufDRs2eGtLzllH\noDzB5sAw02GsY20AM9GEBqxjOruWaWqoUv3Jfdq8eZ+27zqi5PRUx3rswKIp0lnWbLTb0tLs3ApV\nKatgjPKLxmpaaa4y0zvGCjCBB9UyHpRGYGazdmK8Y8aM8RtE464ITevi4mK/aWx2dpYrkdjpcUe6\nH06dlAesWW/j/gbsCbxfc+bM8evuqFVIAOzSIMAzwE0Zikc8GwLPimdW4ugj9jzx9FHnfr6XZjCh\n1YBAQCAgEIdAx1YLcYXCZUAgIBAQCAhcvgiY4AC/tqtXr9amTZs0f/58TzRjrmv3z4eQJ2JrTqjO\nbS5YVdOo5LRspaalKTszRYmOyI3pxLWo3mmt1VRVqbaxRYkpacoaMFCpyU77rRts5hwZ77sJcX/t\ntdfq7bff1q9+9StPjJWWlp5yK9BZYv98Yw/3AwIBgYBAQCAgEBDoWwiwvoGJi6/5VatWeZ/++PeH\nYYgCBb7OcdFjlgZR90SdW0dgE5CgxtrjKt/5hpY+t0w//PZzGnp1sRpifONOApfgmJiu30deVulV\n/03T5qVq5OBMLziItXT+6ug/zFGEJIYDjFGsDXDPdPDgQS1xLh9ZF+KmCWtUGKjs8RBC1xAAZzDG\nmgX3RI899pgKCws1cOBAv+bmvTPXoF1rIZTqTgR4FjwThIgI0fjNPP30016gyDOE1kAI17lvQXf2\nMNQVEAgIBAS6hkAQHHQNt1AqIBAQCAhc1ghAzCA4QGjA3gY33XST9+/bMVBiZGpTQ532rHpM76zf\nrCeXH9ComXdq0pTpuuOqEUpLTfKEaUJCg/ZufltLH/2T1hxsUfboabruPe/VxGEDNCQ70Zvbd4fy\nDib4U6dO9RvNsckhC/5jx455bbqopl3HxhdyBQQCAgGBgEBAICDQnxBg3UNAaLBu3TrPyOWaNRAW\ni7gpQgMf5mBGZobfUBgmuzEKO8MspCn0J2oqj2nXihe0bcM2vYOixc4dqo2XHLiMHVkHJSTE9m1a\ns3yrKqvW64O3lGpQQaaSrTEG006wvhOb8IBxwtRGSDJ9+nS/V9Tjjz/uhQVH3d5XL774gh87ayvy\nhbVUO+CeI9kEB6y3wbS2ttbvdYBlC/tzmWb7OaoIty4yAjwTnk2VU3jC2gALhPLyck8z8Tuw39JF\n7lZoLiAQEAgIXBACQXBwQfCFwgGBgEBA4PJCACKGo95ZCbCh8P79+7323YQJE7yGGWh0eFHszOZb\nGo7r6KHteur5tzTpWIaOOYJ8+sT3atigbKWrUTUVm7Rlw9tu88HnteXoUE1IGKWFjkJOTOoImdzx\nZ0Of0YorKCjwC34YAbt37/ZpCBU6PKaONxlyBgQCAgGBgEBAICDQBxCwtQ9dRalg7dq13rWhdR0N\nY6wN2NsAK4PUlNQzLBa7uoZoctYNNZWHVHXimGvqgI4dSlLZyZj/dN92QqLSMp3LoYxkpbk9jJua\nY26JrF9nxInNSnFLp5NVdRpU1xRTzjgjw7kvGAM4IABgXYTbFawvYJRidTF8+HCvWQ2jFKbp22+v\ncJYIU701AjVTtqs4nLtn/fOuvXOstxFWseYmgO/QoUM1duxY/671z9H33VHx++fZbNsW2wOFkfDs\neIZ8HxC4hd9C332+oecBgcsVgSA4uFyffBh3QCAgEBDoMgIJfiNhzNI5IBhLSkq86XRnFsMJjvgc\nmDNQKWmp2rv9qDv+j/ZumKIpCxZqYWqmRmbUaseyx/XGC0/pV0vfcb0dqTELczU037kzynDUbw8Q\noWgLLlq0yI8LNwRGmHVmXF2GNRQMCAQEAgIBgYBAQKBXIsA6AI1hFAuef/55LziAWY4GPoIDmLlZ\nWVmeoe4tDZJiLkkuhFme4AQDSSkZ7kjxmCR5Nyf4KnJM+KQUNTc2qK7qqDs6Adn4TGUPH6S0lGS3\n+0DnAmOx8ZjwAEYo+zzgQgdNa/Y4YG344IMPemtUtOVNAcPKdq7Vyy8375odWBkcPnzYCwwMCdxD\n4U6T94wQcDVkLl1sz4BnwrPhGVlA2MMzRDkJwQLPlmBlLF+IAwIBgYBAb0UgCA5665MJ/QoIBAQC\nAr0Qgdhit8UTzps3b/YLY7TsjHjpWJdj1gKJjujNG3u9Jh+u06fn/UyvHsxUTXO6Hv792xqcXKVB\nE5r09B+Xa9krm121Tbrrc7fo5jsXqCjLadbRkCNguzvgN3bmzJneRy8WB2jTGfEWFvjdjXaoLyAQ\nEAgIBAQCAn0DAYQGDQ2N3lXMk08+qaKiIs8EZI8nzmGgwxRkPQSjPNEx/bu6brDVTXp2poZNmKqs\nNTFt8yRnWdBS6RjxaZlqrKvW9Gtu0bV3f1RzR2aqIKNZ1c6SwAsbnDDDsZ5PAYszI3iVjY11ysgr\nUe6Q0RqalxETHHRhLcW4sDxgrIyZtRJM0dmzZ3sGN/tFEbBKRYiA73cELCF0HgGz8CW2gHso1qsB\nU0Ok98Q8E54Nz8hCW8/Q7oU4IBAQCAj0BQSC4KAvPKXQx4BAQCAg0AsQMAY6MSa3bNTGBnjFxcVd\nIl4SEt0me9kjNHLMFL3rfe/S4cedy6INR7XtV69oTvEBJR5N0vPPrNTa8gLljRmnRdfP0LwrSjQg\n1RGs3YyHEfcs9EeNGqU333zzlE9SG3c3NxmqCwgEBAICAYGAQECgjyCA4KCi4qi3NEDDHvcjWBzg\n3x/GOEx0O2AeXpBP/1bJQWrGQBWOnqvRY45qhJ5TavpAJSfUOMWJGAmflJzp0pwbx+kTNHFUjprr\nGpWU6MQEMOlbtZqj8NLv5NQMpaSnyi2luhxMcMA4GTNui3JycryVJhYHFhAc7Nq1S7m5uac0rW29\nZXlC3D4CrD8RylRXV/vYcoI3LqICloZI74l5JjwbnpGF6DPkmYYQEAgIBAT6GgJBcNDXnljob0Ag\nIBAQuIQIsOCFeMZ/7b59+zRy5Ejl5eedIl66QsTkF4/WNe/7lJat+JH+8MqzKh35v/U//iY2SCap\nMfPv1bCpt2vuxNGaMMiJDHpw0Y3GIK6XIK5xR8Bin/EyLsbelfFdwscVmg4IBAQCAgGBgEBA4AIQ\nYO7nQGt4y5Yt2r59u6/txIkTnkE4ZcoU76YIRiGHtzZw2viErq8ZYlz95PQ85ZZcp/mzy/TZ+6Rv\nvTxAjS3lSq87qRbHl9y2YoNWvvQjjfvDVzVoxDANz3aCASc4OHfw9gf07tzZznOXsSE4YLwc+G9H\nkBJ10YLl5po1azRu3Di/ZxQ4ErqOy3k61Y9u23vX1Nx0amNdG57tMxFwNER6T8wziX4D6FnMWqnB\n0xb2XMOz6z3PLPQkIBAQOD8C3a20ef4WQ46AQEAgIBAQ6LMI2IIXAhqimQ2FcwbmdJEIjBGtSSk5\nGjhklq65fp6+dOdk1TYWu83+sjWypNRtjyznOmiOPvWBq1VclOstDSB5eyqgOYfWHIKDo0ePekYB\n5zbunmo31BsQCAgEBAICAYGAQO9EgDUAigR79uzx7nfoJcxb3POYWxKEBmZpAFOwWxiDzt1RYpKz\nhJw8Rzfc+33dP6lOMwY1qhZXSG6BVN9ywvVkg1564XUtfnqVTrD9gesXbpLoX9tH9/TNxmhMbMaP\npjXWBVhvgg1+3REe1NXV+XUUuIXQcQT82tNteA3jmfMQ+iYCPDt7huE59s1nGHodELjcEQgWB5f7\nGxDGHxAICAQEOoiAJ2Dc4hdGOpvd4a6IjQARHnSdQHaEUGK6kjJHaPrsSaqrnqoH3lrq4iolJLKx\n2JUaPXqsFswbq4KBsY46erydgEffCxMrIDhAa46xHjt27JSWly30odvab7+dboXkgEBAICAQEAgI\nBAT6JAI2/yM42Llzpz8QEJSUlPi9DVgHYa0YFRx030BjexPkDpusqRkpun39C0pxmy6vfr5Bhell\n2n/ikHLy9+uhf/2Dtm2v0OQZQzV5eL4GpUHiX9h6qKNjMMGBuSxCcHDllVd6y4wDBw5o27Ztqqmu\nUZNjfpO36+vFjvao/+SzdbfF/Wdkl9dI7PlZfHmNPow2IBAQ6A8IBIuD/vAUwxgCAgGBgEAPI2CL\nXTRmTHBw8uRJb44Lsdz1EJMCwIxPSnXm7mmpcfsXxEsJztS4gpF/OlwYkcwYCZgYwxRgrDAKzrQ4\niLksMDz6Rey3UETocvrfaUzDWUCgryBw+rfZfo9P5znj03FGgdN5zkgOFwGBgEC/QICZrjOBeZ71\nAJaWhw4dUllZmWd+syEyextEBQY9wRiPMdqTlJZdrJs+9ne69ZZ7NaduvzJy8qUU6URFhlPiWKqT\nBxbrv/2f57R05R41XyQNB7M6iLosysvLU2lpqceIPQ7ArK7eWRw0NXscO4N9X8sbvya8kP5TF6Gz\n7+uFtBnK9iwCp57pmcRLzzYaag8IBAQCAt2AQLA46AYQQxUBgYBAQOByQsAWvhCMENMcFxRanN/P\n2nLt2LRL69fs8hv7pTpz9xZnni29o30H9mnVhn3KmTxImTlpzhrgtNY/tHFtVYWOlx/SwYpmJadn\naUTpCGWmJLoNBLvWKxsXAgMC1zADeoIh0LUehlIBgYDA2Qg4weF5f/Pdlefs1kNKQCAg0DcQcF+B\nDnfUGMGsc1gTYGmJG0OUCmCQ444HwYEpHLBe6KnARsjZg6dqstvv4FP3366n1u/Wtr1lSktuUHVV\no1sH7dGG557VwokDNWJogSYNy1ZGqtskuYcDY+ZAeIDVAa6bbJ8DcMJ6s7a2Vg2NDUpK7vn+9PBw\nz1l9dz1/W2f72MsPYkKEczYebvZyBGLPMPpsu+t96eUDD90LCAQE+gECQXDQDx5iGEJAICAQELiY\nCJigAF+2aODhu7ZrgUW0Ez40HNfJstV6/j9e1DcfekUlhc5vb420e+cO5bkcr76xVG9U5+vnX7hB\nRTlFXvsqwRVtbml0Gmy12r9jjda8/qyeXNag/HEz9NE/f79G5KYpm0ydYBDYAh7mAGNkXBC7VVXV\nnmEAQRwVHlj+ro397FLdXd/ZLbSmwNeI0S8+ocfbjWuPZ9KDvJWzhm3jM2LNMli6XV+KmD70ln4w\nfq/Z2Ppu0C/DrKf7SDvWnrXZuefhXKhhHdTo9iNJxGIo0R9RFl5Li/MR7TaZrG9ocm0lKdExsNhE\n9IyxuX40NzWqscnV5+ShKWkpSvLPqHO9uZS5wc8wtPhS9ie0fakQOP32nz6L9KXNxMj9fnqKm0Xm\n96gywBnfgLhx2++JMqx3EBygRU+ICg5sbUBd56ovrvpOXSa4fQtalK0xc+YqvzBBh77xI73w1loV\nDMvT3j3lOny0Tgl7fqE/PZ6tIw15+i/3ztDIwdmujZ6dcxkvQgOzOmDfKywxbK2IoAULVdZTCFlI\n70mcOgVqN2XmPUFIwvtlYyOOvhd23laT7gmdc7nqqg+hjyMQnmEff4Ch+wGByxyBIDi4zF+AMPyA\nQEAgINBRBIyAJoYgggCEkK6vq3dVdJ2qObJ3i15/+H9rzZ6tyikarforP61vL8rUlKLD+ou//Zm2\nb1yp5H3b9PoNwzUgv1ATBjlirOWYKvZu0J9+8YDeXr9Dq/cc1Z4NObruI8N1sqZJTTkdHdWZ+Zoc\nY7G6uton7tq1S7/85S+9Bh0EIX6MGTMCBMYfH4xYJP30/dMEe1v3fT5XF7W1ez9Sn9VreaPXtEuI\nplm+2J3TbVie+Px2bfej5ePPXUO+39EybZWL3o8/h5C2tPj4rPZcBp/WSmC3e7/12Vhfom1YmrVl\n12wk6auNlLV7xLFk4tOH1REfx+ex+9H6SIvvV/z9+Hrsuq36rKzVGc1j5SzmHsGufRzB9Kx7rWOO\nT+e6uwJ9IHRFa7eluUYtDYf19svL9Nbr61WZN1tXzp+ia64cLZyomU/OmrIt2rN5tR5ZvE4Zw6Zq\n9IyrNN9ZMQ3OS/eMdvpQW3VcO1c8reXvHNa6fUl614fu1phRRRo+EL/cvou9+g9j4B0AR0L0fejV\nHQ+dCwj0IAKxNYucMkC9lixZ4l3nDBs2zO9PAIN70KBB/nt4ri4YY7iysvJUtvx8t5eAK8vvjd+a\n/d5sjXQqY7edtM65aQUaMGK+PvT/VShtWJK++k+PKSs9xa3FDuPzUfvWLdFbtYf06LCv6qpZk3Tl\nmMxu60F8Rfbtjn57cnJzvMWBCQ7ApaKiwgsP2P8AAUN/DC+99JKeeeYZ/x6w5wWCpcLCwlPv2dCh\nQ8U7Y5idE4M+MN+cs//h5vkRCM/4/BiFHAGBgECvQSAIDnrNowgdCQgEBAICvR8BCGIChDIEYFVV\nlSpPVDoNss4LDtD+bazer91b1+rJ/3hKGw5kOGLzat108wJdsyBXE/MP6D1zX9arL72qDbsa9MKL\na5QzoFjDFo1UduNxVR3drbUbD2rfkSrlF2To1WPlqjx+0msLW2+IO7M2b6iPbfpsboogBNGW27t3\nrx/38OHDPaMA4o9NoSEOjQiEODZ8LI1C5zuPMSRjDGnfSKSMlbU4Wh9plh5t19KsLmNmWNn4+5Yv\nWp/liaa1lc/qtDhaztLom/XB7ts9u24r9s+tlVvb5v3We1aXxZY3/trSLY6/H72O5jlf36Pl4s9j\n/PjTz8nqPStug3FPXRZi+ann9PsU/76Rx+qlnF1bGvntvK37di+aL76O+Ou26iGto8HqIz/t8j1B\nYGcblHesHmdl0HBMe7e+oz99839qzdTP6L/kZGrC1BIVpiUozVkVODsCHTu0Q5vffEK//fsHlH3r\nlzTj+GCNHpblBQexdppVe8IJDBY/qRdf2qSfv5ajiTcuUuGwId4Sw6Hbse5colxgiUYv/tfXrl3r\nLab4jpFuIXpuaRa3dS8+Lf6ash1JaytPW2XbyteRtK7k6Y4y8XWcdd36uzaM48ccnz/+vpWzfBaf\nL5+Vi88XLR9/L/76jLzuFfLC1WjF7jyaJ/aatf2uRfPFtxN/fa680XvtnVsXo/dj82OC/028/fbb\nev311zVu3DgNHTZUQ4uGeu34zMxMpaWl+TmdeR2LStI459sEExxtcpQlLKBMwLfKBAfWpsWWr9vj\nhBQlZxSodNqVml9xTHet3qkteyu0dcc+5+oxSYd3rVOlOwaOnKmWxmoNL5yngqxU9bTXInBCKAB2\n0W842O3ctdOvGcHPrDe7HZdLVCHvF8olq1at0ve+9z3fC3CYPXu2Ro4cqREjRghBFQeCJnuv7H0D\nLw5TTvHvjy1iL9GYQrMBgYBAQCAgEBCIIhAEB1E0wnlAICAQEAgInBMBI4ghePBhe9RpkR05csS5\nDYpRORBQlqf9imLs/OamBlVseVHrV72mnywvlnMwomlDSnTXTRM0cUy+cuuH6IMLRivt5BZtWJmk\nx3/8vAY25+nq+cWOUVip2uo6pc75hG4fdExjBu1X7cnljrh3PnQd78LYFxa335cz73jG26EyTwRy\nBwIXYQGEH8wGBAgQfggOTHsMYplxQxzHGBQxhgpuX9ingTRLt3OLacPOLbY0i0n3wUXUSYi2FT23\nOiyO5iUfgXt2bvctPVouPh/Xls/KWT1WLlrGzq2clbG8Vpddx+e3cjA/LY/VYQxRKxOPAUS81c89\nDtLsnPIwgUjjmds9Xyj8ueQIvOc97/Huwc7/LaGr/O7qVHOyRhvc1YG1P9SOnbO180iD8wee6piB\n/HAaVLZ/n95Z+oAaJg7V/p079dre1br71tEaV5qnFJclIaFaNcf3avn3Xtbm+l0qmZCvuoZaNbV0\n9ity6eDDjcpbb72l3bt3e8Yd+NnBd8rwtDRi+51x3w67z0jsvKOxjd7qsjosRgCTEHERZf2ifstD\nmp1bbO1zHb1v6dE4vkx796iH8dt964uVb8sSKdq29cXKWzmuo+d2Pxq3dz+a7itxf6xfVt76EM1r\n9+LTuI6W55pgacyWrd2NpJ2JMfn9M/N5Y++UT3MFrS9ttU+e+Pvks7KcWz/i09uqL5o/WoflbasO\n35j7wz2sBbZu3arHH3/cks+IFyxY4AUKo0eP1qhRo0QMs5f5njkCa0TmDgvG+DXBAenWB8vTc3GC\nUvImacbsRv31xzbqOz9dovVbWpST2ajK5lRlFQ3Tcz//mtJqP6Ex06ZqXmmKCjMRovLEuz9EnwGW\nmVGlCubYlStWquJohV83gtfFw6n7xxqt0dYmvB8IbEtLS/1t3pX169dr+fLl0eynzq+//nqNKnHv\nWOlojRkzRiUlJf59411j3RlCQCAgEBAICAQEehMCQXDQm55G6EtAICAQEOjFCBhhSBfZ/A7Cetmy\nZcpzlgfNEWL6vEOAEZfgtPfqjuntF17UqpdedkX2aca7/1rX3XCzJhdlKt/5GElMyNTs29+vsqpk\n/cuTP3Z5dqnsyCit3XmDrhw+TMWTcnTf0Cyl129T45Fjyk5LVn0rc7uzhLExj/DDu2XrFk/UXnHF\nFV4DGiIYk/OvfOUrnmmwefNmL0A4dOiQcnJyPKMBwo8DrTFjYhtDLopHR9KsL23lpa5oevTc2mkr\nze51pHx8HisbX68R/qTH37My8XFb+dpKs3Lx9+yatu3c8sbHbd1vK41ynU3vSFuWpyt1R8twblif\nq6/na8/utxXTBke8kMbag7ln9y2Nazu352H12D27Hx9H7/tK3B/qgMH03HPPec1Ua9PutxcnJKQr\nKb3YuYPI000jpH/fI5WVH9bW3RUaPaBAuU5w0NJQriN7yrThD24z9dFO87hxv9tEZZXKjt6sY07G\nNMjxqVtqj6iifIfeKKrXut0zlVk7z/kHz9OQXMdwbxXYtdeH3pKOliuWUAg72bSVb5E9G+tjPPbk\nsWB5LY9dWz2Wj9jytJXGvWi90fxtlYvet/rOlc/6ZXmJ20ojvb16uEeI3qeO+BC9b/dII6/lbyuP\n5Y1VGfteWX7uWRlLszrtXnw619E8bF0rZQAAQABJREFUVn80tjykxZe3fJZu19HYjcgVjKVE81lf\no3k5j+aJv9fe/fgyXFtafGx1mvAhWmc07+lzn8MXszSrg2uYuVgcEFjDkGbuB/ntHDx40LvT2b59\nu7/PvM8cT17mdr5Phw8f9pYJ7IF0ikHuvo/x7Vm7PRVbe9mFJZpy/Z/ro5UZKi2o1e+XVup4dbmq\njh33TR8ur9ayFbs1LjfVCQ6y3Ivnks9+zbulm/SJZ8UBnghWCMwre/bs8fiBMfet/93S8CWuhN8H\nY8RajvfDFBLAgHcEQYkdpJEXJRQs7E6eOKkTJ074DaRZf/LtZi2J8KC9390lHm5ovrsQ6MHfYnd1\nMdQTEAgIBAQMgSA4MCRCHBAICAQEAgLnRQDGAgQfZuj4BobQOXjooCcIMb/uCDEYWyvzt0lVlXXO\nQiBDs66YpOuunat582eqMCtF6Fu1JCUrf8wMjZu0V59xGwJunlrg2nSa4/WO05daqKzcQk0pkBor\njmjPEefa1/WLWqOhs+tyCLiNGzd6ore0tNT75cW0HqIPCwtiIxIhEGEkYIEADmiwgwuMO5gMEIyG\nh8XWt/hrS++puCfaszrbIm7tXk+NJ75e2murH13NF1+u117DAIq+5K0/AI/HWb+G2Cg8c5BircxP\nww1GLwwPuya3ncPo4b4JFuye3Y9ek+b+u+M0Q5quuFSf7s98Hq5jB+Vpg98RWpod/ZZQTs5tR0Jy\nngYPKdDEq6Wi3zrBweEKbdxapmtKB0q5zo1E9SEdLj+q18nuLJsampwvcB3XwfLjKncuywty3Ybs\nlU5wULZdy3RQdYlzNWL4TCc0yFau/xjRUO8PMJtwIYd7DCyieF4WDOvoM+Me18bkt3t2zX3OLd3y\nn0qPPVguTwXy2kGilbU67Toax+ePv2eVx+ezOqPtxJdt69r/TOL6aXVYG9Fy8fei122dR/vV1n1r\nI3qPtGi5+DzxeePv27XF58rPPdqKz2vtk273iaPnVoZ3i3S+GVafMUxhqjc2uM3KnTvC3hj4ncC0\n5TtpexpxHh1PW/2+8sorvSswGOKMkW+WP1xZytvRVtmeSWtRctoA5RVP0eSxI1WxPVd/WN7qSqnV\nfeTJqgZt23tcNbUNPdOF+FqRPTksDJv42/66NQ/5+nqw3wMxwSwtiFkvEhAWxB+sE83NFb8l1pLM\nf7yXXFtZX0H4ExAICAQE+jgC9o3s2e++Jz7U4ucWo3ZiwJ2vfbdy9TJ1/vb9malnXpYgOOgZXEOt\nAYGAQECgXyFgBDHuCiAI0cIrLi72GmWVxyu9lhXMco7zhRit6LTRMot02+f/QQtr6/TndQkakFOg\nLKcRl5rS6qYikQ30BmvqDe/Tt3Ys0klHCCelZTlN2kKlpbh7EGqusiYXw7pohhiNazz+Ou72WZe4\n+mBfA6wNZsyY4YUC+K39wx/+4BkFpF3vTMyvvfZaz0BYt26dFzQsXrzYWyXMnTtX06ZNEwwGXBxA\nLEbDuRZMtqiJz99WejRPV86p0/rS1fpPlQPkGM18qiv+nn8eZzL0T5U5lbN3n4ARfTasor2NT/fX\n7g1k8WkhWr67x95WfdbPtu5Zn9qKWSb7RbMbr9URn493md8+oa3620qLr6O9a8pSP8wS8yneXt6z\n03nR0lQwxGlqXnGnUl99TPucdUHDm5v1/quGOR/fUvWRrdpffUTbXOERJ447jVw2C92mHXv3a+/B\nSo0dmKXKw0dUtnWdCo+2KOv6Yl2xaIIGZaUJndkYOXF2y70tBewQGMyaNUtjx471DKjo87yQZ9SR\nsZ6r/rbu2e+DuqP99G1B/0V+Sx1p3/LQltXXVruW70LiaL3RttpK70w70fLRcqRH8Yre68p5e+3E\n19XRfPHlzncdX2/0mnM7qCd6z4QY0XTLa7G1zTX5YcRysF/RAw88oCVug+T4wNoFZQisC2Do8lsi\noBBgQobo/gbcs/b4LvJs7D3g3sUMrIDq3Tqq1jGeExJi8w9rNUKKs7jKK8hUSk9vcODa8hiwCnP/\nwcbwAlvcQE2dOlUlJSVeqeKcggXf897/x94vBGYIkp599lm/foz2fPDgId46F8WToqIi/33G9SUK\nJ6yjEZLbwR4HUYFDtJ5w3g8RiP1E++HAwpACAmcjwBzMN7PHXbG5RX8LCkVxXWhsjK2hWuW5cXfd\nnNXs3Nl616TOcfKZpPtZeS/XhCA4uFyffBh3QCAgEBDoJAJGGMPgQ5seIgdC6NixY1qzZo0XGqDp\nysKgIwR0QmKysguGO1sCaUibfWHaT1bmwAJ/DI7P49qxcPrMUjoXw1zA/zHuh7Zt26bbbrtN48eP\n94QdixwIPHzV4jv8nXfe8YIBNleEyUCMwGDfvn2ewYArBDYoxeQcJh4uncAJLUWIZfBpK7SVDo5t\npbdVvjNpvk4Hr2cYt9OfztR3vry01xPjOKtdoI2uFt21McQtr/WlI+8oedt7Bj4dxmbc44yOM9pG\nNN36ciFxW/W119cLaSe+bFvtxufp7DV18l2BAZPkVvVR3DpWV6JyhwzVyAlzNCJtiXYfOKhXytbp\n6Mfn6XhNgsp3b9Hxo2W+quKJY5XtLJ02rT6otZsPaOqkw1o4JlXlR8q0Y/0ftf+kdNvowU54WKqs\nDOczjRB9p2IpvfIv3xe+zXyXcLMCodYRLPkEuE/NRQ32rrbXv/bfMxi0F7WrHW7MxhQtED8+xmVp\n0XMr0/64Lcfp2Nqz+PSd2Jm1E5/uv1ndjGF8W/HjaK+P1rdofs7jry0fsd07Fbd+h6PXNreZ4AAB\nAFrexrRF8cEECjB9YXJzjZCAvPyOCKRxH+a3pVk7pHPYtS9wUf8kqKGq3H3fVmrpig16ceUWNdc7\n8ykXkul/1UQNGzJVi2YOVUFOzG1QT3/L/HvgvieGO33h2873qLCw0B+2FuJ71ZcDz51xmqUNwtpP\nfOIT/n1ACI4iTHpGul8rI4ziu4xFGG7kOEdgABYcvFvEYBX/W+rLGIW+BwQCApcnAuxjWFW2Udt2\n7NUba/c6l8ao+GG1n6/x06doyvTxKhyQqLryXTq4Y61Wbm/W0WPVGpBQoaasUmXkj9B1czLc/LZL\nq1/foJr0ZNWxfnJHU4uz7M8q1A23z1fLsZ3av+Y17W8q0DFnYddcc0yNro3M7HzNmjtCtWW7dXjn\nDu074YQWAwpVNHqmZkwcpiLnE7mlpkxbV653+yhu0VFnXVzvDKWdeqRGTJyrcePHaXRRmlMoekt7\ntm/W7oTpGjt6pKaPzVN9+WZt31Gml96u1ZXXTNTUaSOV6vqV2FsXp930CgbBQTcBGaoJCAQEAgKX\nAwIQNBwQfBA5MMchnJcuXercY4zyLjI6g8NZBDf1x1fgJuMzeLNt5GlVsjvFxLX8xGfVF1+/u4Y5\nsHPnTs/8h6iDwIWxQJg8ebI/RzCA7+OHHnrI38f6AOHClClTvJk5LlawTkDr7MEHH/T3rnfWCRwQ\nhWx6B/MBQQT4GXFosW+sC3/AkONC64lv+lS9rQjGPYX47Oe9PutZn7dEz2SwcXVH7dExgX/0uqv1\nd0cdtN1d9cSP40Lrbas8aTBM+JYkud8GoTPvsyuuzFz3uy0erREpg3Sk4oDzV7RS5U4D98jJJB3Z\nuUEnj5T7esdPHe8EhEe1YfU6vbTmoK6eXqb6hnwnODiqLW86hpfLNWxIrts0ebD73caWyWd8Q/i9\n+Zo618fWImc8l86M0cqfL+bbApYchPO1EX0e8Xmj96Ln1gfyt5Vu988Xx7dn+c9dJ987y9k9MfWd\n4Vqre6rt+Voc/h0Bo73ndG6cL6z7bdXdXj8urCVXuvV9sPfJVhFcWxoMXuZe5mET+jPvIyTAXREK\nECgO4C6GvBaYu9EOpxzKEjCEKUfge4WLmUsRwBfrgpPle7Thtd/qiReW6em33N4NGSeVlJKm3Jxs\nnayYr6FDpmvu5CEqyG7jW9YDHQdv8EEQY+8AMTia+x2uOQzHHujGRavSxkKDKIpcc801p4RMJghI\nTnF7HDjXm4yfd5CD77NhYDhwTbB31l+EP/0XAR73GYuL/jvUMLLLCYHYi42g4NieFVr+3JP69Dcf\nPgOAT/3XB/XhIaOUk5Whk4d3aN3i7+gf/z1Ry3a83JrvE5r4/kX6TV6Ktix7Sfd+8d/OKB+7+JiW\nbJ6k5h3v6IVPfkaPD52kVes2tOZj/Xu3/uH/LlLVple1+nu/0X/4O1dq0ef/Sv/9LxY5F6U5Tri+\nS+uXPKJv/90PFdv9KFb8lj//gT56T46Gu7n/wObXteQXf62/qf22/vX+W1Q6LFWVW17X8mff0me/\neVI//M1faIwTHCS7Ybca+rX2of9FQXDQ/55pGFFAICAQEOgxBCBojCkFUQTzHOL561//uq6++mpN\nnz7NE4jGtDpfRzpEIEH8t1WRSycg4U92p44V72ftxBQEG9xppxy3WgOEmhG6zz73rLZt3abrrrvO\nWwignWjjgOF///33a+3atXr44Yf19NNPq7y8XLfffrvXGktxhCFm+KNHj9att96q/fv3a+vWrd4S\n44EHfum0zGKbKOPCiHyYrVMnDAojFq1PvSWO71f8dW/pZ3v9OFd/z3WvvfouZnpv79+5sOhK3ynD\nbw0GCkwVNDg7F9yKPd25OhtcopkzUlS56og2la3WwSOf0470FB3b9Kjbv2C8q/Lduvldd+nohrWq\neeQZvbxstw7M2+z2OsjSnv1OcLCOVudrSMFIjRnhNIzZ3yA+tPc9is/XznWHvnntlD1XMhgiNAA/\nvi1ouIJnV9vrynNsq3/dVU+0bi+6gTbtpkAfe6KfXeled/eF+uwd6I4xdkcdhkt31XWuerjH74Dv\nC2sWzrEc5DcCc5s5mBhLA9Yy5Oc3hEY412iFM59f7xQAmLuZ97ds2eKHwJ5IHNRhGNvYej5272zV\nNm1xmpY//b+vaP/RKqW6hVBdS7qaGk5q784Eff1fPqrrrnHrjQznBq7nO3SqhZrqGuH20dZPfM+x\nOOAAd4QI3ON71dcDz57x8c6gbIJFgX13GR8HAgPGa4KDaGznlLd8/QGXvv5cQ/8DAgGBriJgFHui\n+zYWaPIVH9SDT3xBo4dmKrF6v1779V9qb8IuPfPWLk0tGue+kY5mdy6KC4Ye0IzBN+j2D35M05xS\nXn5SjTY//QPtqi7Rx77xoO65fqhSKzfp2X/9tLYXfElN4xZp9KBMVRxw39gp0oDa6Xrfpz6pj3xw\niva9/qg2Ln9df/zFFo2dcbOu+dkf9YnMHc618F595Zv/oY/fPskpOuZpYG2jhsy+Xf/5327XD+eN\nUnL9fh3c8Jz+/U+un8+/ratm36GSK67RwvqvS+9/RGumN6go74h2P7JYB/Y36tPf+4yzNhgr7Py8\nl6OuQtZHyl3MdUQfgSR0MyAQEAgIBATaQwDiGKIGIgjiDw0rDgLEND7/0cCHOIQA7zFiuoWNGZ1f\n3yanpVxdp+qaOjU11quxifNqVdemylk1OkLs3Gbf9K+mpkZ79+7VqpWrPAPgescggLEPwwBijgAh\nCCOOcOTIEeGOCPdMuCCaONG5A3D7GUAUo5nIuIkRPFAeJsWBAwe0evVqz6CgvLkvsnwwNHp7YFzI\nZs4vjun8SHzdnS923hI9+g6et/WuZegpLLrWm86X6mr/+abwe+H70rXvRpbSsgZr/JQx2l6+Vtos\n7dy2RYnHklW17YSOHHdEwqzJGjtuqk7UVWqSG9oB7df+neu1fkOKNuzaqxg78CoNKSzS4KwEt0l7\nlDvtGJDuG3Pi6EEdrXQm2PVJGj6q2LmjSFWq0Unngauhrkonjx125RtV05SsEZTPcAyj85Tr6G37\nPvM9wVc2360LCV19lhfSZkfLxveN606/N/6bFrOaiK+vo/3oiXwwI3tr6Fac3M/LC4EucLDn6lOL\n2xuJTZr5vvCbQCDA3Mx6pa3fB98fDu7BEIaZO2HCBJWWlvp5m3meNIQKuDfEUuHiPy+38XR9pXa+\n+YaWP+MsHJdv0kAnIFVCuhrqT6pk0g2aNP1aXbdgoqZNGKT0pOh37ALB7kDxquoqv5+E/R6x1AB3\n2zvCWx+455HgcO7rgXfP3hPeC8aKFYsJk3iXSOcw4QGxHdy3c2L7hlPvud7rvo5b6H9AICDQvxFI\ndPsUZg4aqWEDmzUgOVd5zi1R7eEKZdRuV72bN/cdPqmGpmbn4scpuKhGKTklKi2epwULr9GkUQVK\nOb5NT/z8MZ0Y+l9UMG2Kpl1RorQjzVrryOXq4qFqGV3i5r1knXDrpaZjUvF0N99ddbXmzx2vA03r\nlFqzSf/23RWaddMEzZ4/X1My85RQV+9A/0e3L+NfqOxki3JSneuikgK15CSpaPAAtTjrwxrnmrjm\nyEbt2rFbx5xB4dDCMRo16Wp9/O4nVbZlqZ5urNSeZ/dp9PyrdfPCiRpVnA9p7EIHCQGft2/+6S5a\npW+OPvQ6IBAQCAgEBDqNgBE6EH8w1wcXDtYnP/lJbdiwwWuZlZSUeMFBpyvuVAHnj7ihyjHxG3X8\nwGHtLzumGseUq68+roN7DyrP0aOJAzKUn5PhiLK2J3OIMog0hAbLli3zAgGYA2YRAJOBwwhDGAXc\nh9lPuZdfflmf/vSn9c///M8+DSwI5EfrDGsMNkqGsbBnzx698MILeuKJJ/Td737XCxve85736Kab\nbtKkSZO88IU6OSxEzy2tv8Zgxr+eEEr0V8z607h4/sZggXkCI6YzIfarQds+T6MnzVTx7kpXfI/W\nLntD+zKdsHO3E/glDda0seM1eNAIDRw+SKW3ua3Xd1do964VevYpZ6GwcYOODJqkcTfNUtHQwXJG\nzM6Xqqv51E/SMftPHNL6ZY/q1RUVWrE/W1/82/s1dmSh8hPPw7R241NCkyqP7ta6157Qy6uqtLWy\nQJ//m/s0dliuBiKgiPz2OzP2aF6+GYajCWG439a3xH5v/rfXir+dR+vsK+f0vSsB2LtYtCvNnVWm\nq/0+q6KLksCPoe8wNMEWBq4JCBCoIewfM2aMNm3a5C0QYPLaM+B3YkJ8LAkox/1Fixb5MszxMMAR\nHmChUFFR4S0QyGd19OxjAHvWCdWqc0yVp3/6H/r5rx/V8JKhOryrTCn5g5zv5T2aetVC3fb+T2ha\nSb4Guz2eL+bMCg5gxz5PfIsICGrADaY660YwhpHe1nepZ/Hr/toZL99aOxibvW+0ZkIBWzcTczB2\nOyyN/JbGeQgBgYBAQKCvIpDo1vJD3B6ARw/t0+E1b2rp/kPauX671v1MarxbKnTWwcnuW9jihAdJ\nidUaNP2TKpo4X9dMGeFcGCWqoindzRNOAdAtO9Ld+rnOKfk1Vteq3i31srLTnHvSbC98rncJ9e9I\n8748V9MXzNagLHd//BjV1N4gjbtRU8dN1/wJBUqtL1Kec+F3jQO01lnEHT7eqKljxmlI0n63L8JW\nvblkqw6V7dfhioPadeiAc1c6UTUNzapLcq4Kh83UZ++7RY8vfk3/7X99X0MW/LVmzrlV10wapEED\nXCe7Zwnf6x91EBz0+kcUOhgQCAgEBHoHAlEiD2IIQskT4kOLdMMNN+j111/3rnxeffVVv3mw7RHQ\n3b2HPdR4fKd2blmu//uw2wDVbXxUXbFDK5dvV01huR788QkVlyzQmAmzdd97JmtwDsz/s/lyMBRO\nnqzymx6zJwGWA1hLQORiMcFhggMIQcaMSwOIPBj+Q4YM8Rp0jPvw4cO68847vQAAwtiYFRCV5CcN\nwnnhwoU+744dO7zA4te//rU3by8pKfFtw9CgXgvGjIhib/f6U+yJ5dMc2v40tDCWTiDQ5fccfqYL\nbAg63AniCjftdVev6dC2NTronJi1rHe+v981QjNmjldWaoaynL/yCdfO1UtP1uu1V7dqQFq5yg5s\nVPGQybptwRhnQZTvSjlawNXb0lSjhpP79Ppzz7g9TNZq9ZZt2rHXWTEkjNOxEw1ydAV+0toPjSdV\nc3yPXn/+eb351iqt275Lu/a7b1L2VB13G7k18kFr7X/7lXT8jv8tJcQ6xLfHhzbqR0hHMoxIy+MF\nJbGrPvfXvpVd6fi53jseDxMIeS6kjfb61RN1ttfW5ZTuNyl0zwyLQvYmYg8irP42b96sbdu2+bkd\nASVztc3ZXDPH86xJZyNlrA1mzZrlz3lW7H9U4L4fuC+COc5hgoOefpa2jjm0dY1WPv1jvXVgl/fL\nPOBguWOmNKnQMVOqJn1Ji25YpNvnDVVuVus+JxfpwTN+cENZAktLcERYgKCFtSJrRtO+JybY74q4\nLwTGaH2mv1ybcIAxMX4OAvk4+A5Hz+2exf4eX+MIBD39LtF2CAGBgEBAoKcQaKg7pvUv/lLrthzU\nK5sSnTVwqQaPK1XVrVL5ELcu94sr9w2lAwn1Ss9CuOws9ZNZtyYrMTlVGUXTVLb5Vb29+7iOr3Bu\n7pqqtOPEXbph3ETNm+Nc/jrrg2ZnVcinM9mVS3EujxLd3j9JKamufIZzheA8BjS4utya2BlAuHZa\nVOci51xQ9bUndNhZELzxxko99+pajZg0T4UFxRpTmKaCwftjAmA657qTmORcgLo4xe+CJh1ylghN\nCc5yLMW53HNZLpcQBAeXy5MO4wwIBAQCAt2AAASOEUqmYZWTk+u08UZ74hz3PUuWLPHMdyMWIaq6\nOzQ31aqm8oBefukpvfHmZo0YO1aDxw9zxFmT1vzmAe2+Y5SaBk5yrozM5QOz/2mqDMIONwNrHCPh\nrbfe8nsWsDdBaWmpZyjASOAwrTjGbIQcZce69iAGsSTA0uKpp57y+xswVlw3UY77MCKoByzYdNnc\nG0BM4+6ITaWXL1+ukpISr73IxozUjUk/ggs0HKnH2gb/EAICAYG2EUhMTlHOsFHKG1zkM9RUbNHO\nsky1OAOGW4YUqnR0sVLdJpVpA9ymZ+PmauCAN1y+nVqzfLfzDd6s6VfmaOK4wY4x6FSWPDnjvndO\ncFBXuUfrlr+ox/7X77WpOFt79zkT6cJ81dY5xmMr8XN2j2LfnObGKqfdtFvvLHtej/7gj9rsrB3K\n9w5TydhhqqtnjxNXsht/1jEG1enenO+bccYnpRv7cboHF+fsfOPsai88JGeA1NWa2i7XU/1uu7X+\nn8r8zLyLRQDzKUJ91iXM84sXL/ZrE+ZpLA9gcHNE51iEACgMUAfrASwQhw8f7udwNkJGcJDv5nKe\nGy4IERyQ1+bonkS4xblnbKqv0I4Na/TkT3+l1bUjXHPObZJze5ae1qgctzfL1TfdommTnWulgrY2\naOm53tkaCfzY3wDlCNJw+4iVpq2JiMEf/Ozdt7jnetd9NVtfiRmfXfMOcZjQgBbtHnH0PNobS4+m\nhfPLBIE+PN9eJk8oDLMrCLCodQz6xvoqbVr8Y73x9jb9KPmv9C9XF6q4sF7HhzlXQ9mJnoFP9SyB\nHYWtJGdagIcArn2A2Z+a7hQDl2qZo5WXkTj6Wl075w6ncDdcY4ZlOEZ+bF8iz7x3a/hm55bQmSHw\n8VVLMz8w1gNOoE1Z7ru+1XDu7jfVV6t8zwt6+5UX9aN/X67/8S+3aVBRrgY01jkXoukuL+Xd0eis\nHaqOauvuch0+0aTiSVOVUX9YDeVuP4SKaqUNytYAJ7C4HEIQHFwOTzmMMSAQEAgIdCMCEDoQSBCA\nMMXT09OclkC2Zs6c6Vv5xje+4bXLYHyTBvM7SmBdaFeYylPzJmvC1aX6w3/c5xYFbADq1gSnVhvO\nPDw1W2npTtNtYKpvLp44QwsRzcO//PznvSYhfUaz0DYtZlymHUcF9B+NOcZNXQgAEBB86EMfEhYW\nzz77rP7xH/9R9913n+644w5vNcD4YShw4O6AGMxynP/EefPmeTdG99xzj3eZAFPjV7/6lX7729+6\nDZtG6sYbb/SujmbPnu2ZGLRLH7oTRw9M+BMQ6BcI8FWAXnAarfmjVTy42G2D7JwVZTghQFGijjg3\nHiUj3AblYwvdbzBBGQNyNbRklgozN/pyQ0cO0c5dTliYNF4TRuWrIJfvRkyLqaG2WlVuXwOV3qkZ\n37pZX5xapmef36b//cNKZ2Z9DmMDvkeuW/VVJ1RVUeYInvfpxr+/RV8dc1hPLd6iH/2/ameCHWvD\ndyL86fUIxM8jvb7Dl0kHo/Mi8yzCAiwBmZtfeeUVP1+PHj1a7373uzV9+nQvVHj88ce1a9cuL7C3\neRq4eMbM0QgJmKexEkTojzABhjfzM9YGMMgpj/AAKwWbn6N96Tb4Wdy4fjXWVWv3G7/X647R8X9W\nSyXDTnhtx4wB1Tp+9CYNGLpIf3X/bE0ozostiFgYXcTA2MEFYQy4s/cTlqdYbkTXTxexSz3aVPz3\nwNaH0UbJE58ver/d84v76NrtRrgREAgIBAQ6gwCrWjdbqdkx4A8ud1YDA+/Wtz5+j667xq3HG3Zo\ns1PkaXHM/DOnJydMdv9a/7vmnFKNUxCsdNZ0mYNv1p2fnqsZw3M0cvgw5Qwu0biRbg8EtvDya/AE\nv08YrPtYna0fT39Brb5mr0DkDPP8nJnghAuN9bUq377MWSZM08R3f1y337RIQ7MqtOuNVUpudFaH\nic6cwdXRXL3LuQJ8SX/333+i6Xf9mb78Vwu16icP6PjSJj0xdbruuMopGAyHz2HtdwatvpU3CA76\n1vMKvQ0IBAQCAr0CAQghiOiY4MBtyOcY4zDSYah/7nOf8wT17//we99XNOhhyHdnSHATepqzUSwu\nzu1UtRC1aCKi6f/GG294Rj4uitiPgD6am6LU1BQ/PgjBaDAi0JgDJhwBi+eff07vvPOOFxAsWrTI\nWw7AbEBYwNHQ4LQFm2KuEUjHdREMCzDknH7AhDh06JC3Rti3b582btzotR3BFjdGCGFoK4SAQECg\nDQTQNFKh0woeruveLz2+PVVHWl3xDHO/79HDs5XsNJoSknM0oGisSocO1CxXoiLpoBJG3KUhE2dq\neF66c13kElsZ/4mpA5Q1eIrmXZ2hyVU1Gp35lt5ZechlOOrIETK1E1ppl6QMp8HkzK2vXjBADbVH\nVZS8Qivz9rtCx6GRQggIBAQuAAHm4mq3oWF5ebl27tzp1x4HDx70FpBovuNmqLTUuUhwv38s/3AF\nSH6E81j9sdcB8zh++ZlbWSOgIX/ttdf6ORnmN/MujG/mauZhBAcW2OcAAQJWhFgj9ERogQFSd0RH\n9qzV7//0vF5+fYVrJkllR04oJTvfCQ2S9IHP3KVrb1johAZuE8pUt0Y4x6epu/vIMyCwDsSSk2dB\nAKcrrrjCYwbGXWKg+5r6xp+2xtdWWodGcxGfX4f6EzJ1PwI847AI6H5cQ42XFIHYK40bnyyV3jhX\nx7cd1sa3X9BTh1OV1VCmTU4P52RWs7Ld+4+lAfkTnFkw8whTSezThzVuk6ORG1TfmKSa5mSlpKWq\nqfaIDm7Zqn1bdysrZ4zu/sAENSbF6HTK+bL8cSYGsfU5botiNTrNP+eyyCkOkc8lJadlqWjCzRqy\nZ7dSXntHLzzRooyk4zqwaYW2by3XWGfQl9hSr90b39G2l5/S8cn/SVPn3KYbr5upUZVbtHLFTv3u\n9y9ofOHNjraYqDRXaRJzdT8OQXDQjx9uGFpAICAQEOgJBIwQIobQhqCGAQ7RiHYZ/v8fe+wx/eD7\nP9CQwUM8IQ5RDbPcGPFWxwX1j0XGeSqgHSNqMSHHdQHMBbQNlyxZ4jUK2ZwYjTjcA9FHxpPsXJ4w\ntmg/6TsCAILVieUCTAkY/xDLMCK+9rWv+Q2TGXNJSYkvQ12UNc1GsKI/1I9QoKhoiF/IYN6PWwUs\nGH7+i1/41Q1WDVdeeaXHzoQbqfhvdIulbsXzPFiG2wGB3o8ABESacguGaNLVd+jZXU9o3xa2Of6w\nBuUO1tB8982CYkjKUlqecxfkTJ0nubsPbndpV41S8eSJynd+wWNyg5iWUnK6EzIMna7ZQ51PU8f4\nP7nNaSM18+U5H4EQu5+SOUg5mQW6sjhBDSdSVbHFfUfO9+FytYcQEAgInImAzbukwuBnPsUyAIH7\nli1b/Jz+u9/9zu8fxLx67733Cqs9LB+Z27EMQLmBeZP9jI4cOeKFBAgGmJOxMkSAgADgqquu8usC\nGN7M5czftIkgwfYhok6EEOyfQBkEDszr1B9dO5w5is5dxcbcpOqyrdqxcrH+9p9w2LDfbQCZoorG\nFGdVmae6k0Od0GCebr51hgYkwYhxHxi3trgYgf7ZUVdb5xUfwNUCmODqKWpx0F3YWBu9Ke7PY+tN\nOIe+BAQCAr0UAWdJi15/cppz/XnLPO1+7lk9+N+/ogdbuzs7XRpemqh8tz8Aq+wEN1+mpGYqNQEl\nOzd3+nxNbhZrVHVziiodnb2n/JgqBzs7hiO7tG7Jz/TIGwtdrpt15c0j1eTqSXVXKY4mTmbe8xVA\nczt3fePdHkbpMcFCgnNTmpKSLByRprg2M7JyNGLYTRq56iFlrPsnfeWvfcOtf5I0RncqNbHRCSm2\na8PiRzRrwW81fupVmjTGud+7eY5OOjdJb3/lEe27a6oqmyeqwJXs72p9QXAQfUfCeUAgIBAQCAh0\nGAEIJIhpCGWIa4hqDq4humHEv/zyy0JzHi16NPiilgcQmxdEZLn2O0IaWxtovy1btswLNWD4X3fd\ndbr66qs9UQtjgINxmIuieKZ8QqJjOrrNkKKBumE4YKmAiyIEEJw/88xiofX4vve9TyUlJd71AUwO\nwysqQDAGCHgUDyv2eefMmaNPfepT3p0STAkECbhewN0Cgg76DQMDjEMICAQEYgjYbz1/5DRd9aF/\nUumt/0M1de4rkThQQ4YNUr6jH5K8BUKKUjKcVcJ/+oam3/lFfck5PU3NylN2boFy01Ni35U2Pi6Q\nQ00u3btO7QzoFKQ+971ockezO0IICAQEOoaArRXs980aA3dEWPjh5o99ho4ePeoZ9h/72MdUWlrq\nlRiYHxEKmNKCuSC08igSRJncCCGmTZvmBQ3jx4/36xXqYG3AeoB5m2tcF2F5QHkEEczN48aN83Nz\nx0bU8VwJbtNI1R/QWy++pof+1//ThHFZ2rUzQcebstVUV6EhxSP1oS9/RVfNLFWJWw6wQkE26v6e\npxG3furGzxDPpuJYhbfkRDnDAmsi1i2srcDQhCr2LC1fiAMCAYGAQECgPyAQm1iSktM0fMa79d5R\nC7Xgrr9Wo7MaQEiQmd6s5Iw8pWS5NblT1NGoWZp9z+81riVfSWnOzbATBKi5XJXH9uuh32zXrC9/\nTP/z3o9r5rBMZdfv1oEbpmjMHzfoH360VccrEzR22k362PoVSh40SukDndKfW+dnDLlSkwZM09o/\nSfl5A5xggcX/ME2cf5d+vGq+c380XJk5A5SZPFkLPvKXeuCWj+iEm2qZFFPT4WukKjN7oHN7mqvS\nmz+oGXNv1r1pQ5UzcIBTKkxWwdibdGvh1Vp5c4MGFw1Sgas+udW6uT88wfbGEAQH7SET0gMCAYGA\nQECgfQTcugC2PUQgjHYI+6jwoKSkxGvsY8aP4ABfw2jd47YIhjfMdYj4ng4wCGAooJG4bt06T+Cj\nmYjvYhgDo0a5jVSd+wKYC/Q/Zm3gFjetFLXF9NOLKdy4GYcF7jN2GBOMC41GNBDx77tq1SovBMBH\nMsx+6mfM9MksEOKtELIHOCZFdpa/j5AFhgV9ghDftm2bZ5TA6EDwAUGOJh/5sHgIQgR7KiG+3BFI\nzcxRPofbhO2s4GkaGFjpKhg+3h1n5WgjwTj/MXbc+VhybVTgkyjX1bLt1RnSAwL9HQHmWeZWXA8h\nMGAO3L17txcYIDxAeA8zv8StO7AuYF7HAoD1CfMzgXMC8zNrAspRD24KYWxTN/MsQnn2QcCqgHnV\n1gW2FmA+Zs1AO9TBXPzQQw95S0vOyU9ey+8b7cof+u3qqT1RpkObntfbb72uH607rJHFDaptStSA\njDo1aJqmX7VI73baj6PdvgYxxUr/getKi10uA8Yc7G2AEIVng8UHAYsD9oxgrYNf6QvGpcu9DAUD\nAgGBgEBA4GIhgJAgY+BgfwwbeY5WM/OUy9Gaxc/YTjsn0THoB181SA3Vx3R0/07tqE5ResMhVZah\n6z9AN3zA0cjOqiB/UL4yB6HvfzokpedpgLNsmJJ/Ok0JzkVwQZE/TqcOcDQAx2i3p4KbclkmxE2h\nWc71aZ47oiE1q1CDnenC4CiNEVcumr+/nAfBQX95kmEcAYGAQEDgIiJgTHSaNOEB5xCFRkQiUEBA\nsHXrVr3wwgueoCwtLdXHP/5x7zsYwpKyHO0Rk+2l05YxBDi3YGnEMBrwt4tG4qOPPupdAEHw33XX\nXV5oYIwBszaA+U+fYerTbnzbdh2N7ZwxoK3ImG644QbPPICA/pu/+RvvugirgqlTp3pBAGXMqiFq\ngQDzg8OsERAyIGhBsxGGBMKP1atX66WXXtJnP/tZP2TcGN1+++2+bvKZZmW8cMPwCXFA4PJAIOYr\nlbG28t/8sO33ahjY9yKaKT6P5T0jjuP+c3mKZoCJ1pr5rLrojL8by2H5iE+Vby0booDA5YjAqd+k\nGzxCdm/J2NikssNlfg5fvHixt8DbvHmz378A68abb77ZC+5h9Nv8TVnmZeZY0jhnbkVogFD/m9/8\npi+H5SEWflgIrlixwm+GPGHCBA10zG6EALF1QbL/RFg9ubl5XuCAUgQWgQTbKBmBPm1eaOArwjeh\nfO9WLf63T+mNjY5DkZyr44ePu80cndajW9vk3vFujZ+1UNOHunVU4wnHuI+5Pzxn2+4blJTi3DE6\nd4epKa6cW49cSOB58YxYb5WVlek3v/mNV2hAGYP9DRDggFvsOcSENxfSXigbEAgIBAQCAn0EAVsP\n+7Wvd6LnaGvrO3Q256fX67E7LjExR3mDRupjdzvXx3/6vv7i375vhXx8x3/+ju792Ac0dkiWMl0K\n871fb7sKY9WfWaetxaPrCxqnR75r1OpcLPk1edRygA6eyuAzxfps4yLJBas/dtV//174yqb/YhNG\nFhAICAQEAgLnQYDJEoI8GiAiCaRzwCRH4wyNeYjzBx54wPn0L/Ia83PnzvXageyN0NnQ1kTN4gGN\nRJgKaAOy8SFWDywW2AwRoh7LAIhZhBrmhgAGwbmEBvF9szEbg4C+cBjTAoKZ+tFOXLt2rdfA+8hH\nPuLdIDB2+sNBPcSU46AP4GcCBM4ZkzE/qBPfzB/4wAe8JQdMi4cfflhPP/20FzDgzxnrBjQorW/x\nfQ/XAYH+j4ARJCzo2x/tqW/IuTL54rFKYLLhQzW2AZr79iVzxBEN7v5ZTbbWn+jcnaW485gXVxen\nuMMZMJ2Vv/0uhzsBgX6NwKnfpBsljHncECH855yDORJBwZe//GVvZYCwoHBwoTIznI9kJ2y3dYfN\np8SkY1HAHkIoEaxcuVL33HPPKctDlAdYEzBvsj5gvUIa6wLKUgfzNHMqxyCn3chciyAf94cE9iZi\nbsc9IeXIHx2Lz9SpP46F0XRYRw/t09KfOcFEiftKNFeq2i2vmlWlE66u1C0v69nf7tSBZQP8N4St\nV879LXF33WaP6fnTNbhkjv7TB9xm8IOy3QaQrrJzF2yz5zZG1ilYdC5fvtznY52H8AWhDNYfPDNb\nw9jaqc0KQ2JAICAQEAgI9B8EbD3cugZue5o5vV4/PfAUZQwYqevv/TtNXPRZffToSdU3uH0PnLvg\nlNQ0DRo6SkOKipWd4fYxcOHseaWtOt0019qP0+1E8p11rzVXW+kure2xnK65P54FwUF/fKphTAGB\ngEBA4CIiwERskzaEJJpm0QDzHEKcmHsw0mHqY4kAUxwtNbTpYeKj3WdMfAhNCE7qtjaonwPNQYhV\nYnwM24GFAXXBUGejYvY1QChRWlrqtfI5p37aIoY5QJvGHLC2ov1v77y9vIwJawbu0z8sDzjY74E0\nxmVCBavbxkdZDhgVJkBAiEA5ysAkQfiBb+U9e/b4uhCSsIcE9VdVVXl3ATBJcBHAOCkD9iEEBAIC\nXUGAb06jGt3mBg219c6yKGYZJOcopK6+TrV1TtvW7XackoxfVrdZa2WZjtUkqa4lQ8VDnEs2t9Ju\ncemNzS6tJlae74Iv775dtfXNqk9wwkH3m0ewEEJA4HJEgHmPOY+5DZc3zGG4FVy5aqWWv7Hcz/tY\n9MHc55jjGPdZbn5jrqQscyjnrBmiMesFLPZ2OjdEzMOsPZgTr7nmGk2ePNlbCaItb3MzcyVrA9Yq\nVhf3qId6mb9ZN9CXkpISzyDH5RGMc8otXLDQ18+6gkC/uhyaq1VXdUJbXQXHGhs8c7/Jb8zu9pNy\n4seaza9pKUenG3iPJt9bqLtun+I1LLsoN/Ct8szAF1wRHIAPOLDWwgoSF1KkcYDjBeHR6XGGAgGB\ngEBAICDQ9xBwtHJKtgaPmuoO1/sW1t3NMcGB2+D4AmbVvgdFL+pxEBz0oocRuhIQCAgEBPoqAsb4\nhjg0whAim8OY8qPHjPbENpsP7t27V9u3b/cuB2Dy4xMXiwDuceC3Pz8/3zO/IcCpl7og3iHyYS7A\nWIDBQNmNGzd6LULc+AwqHKQrZl3hiVY03tAkhIFuB0S/aRNC4Frd1N/ZwFitnI2bGLdFMCfQSoQB\nQXvf/va3PYOfvs+fP99rJ0YZHsacII1z4lTnTqCxCaZlo+rr6r0gAqYjmJY4pgV7HCAsQPgCUwTt\nx+9/P2bS+Zd/+ZeeOUJbw4cXu+dy2jKEPlp/OzvmkD8gcFkh4IQGanLMzKP1qjji/KseOKpjTkAp\np/V7aN8BHcgfqOSBGRqUm62WGvc9ev0XemZ9gdY1TNQ3Pz1Xw/KcmxPnRqTiWJOOHihTxUHKoy98\nUgf3HtDBgU7QmpWu/Byn3Yz5QQgBgX6OgHcIALfaBeZ0uAAI/5nT0eJ//vnn9Q//8A/+PsznO+64\nw7sGYl8BW08wb1OWgzSu7R7zJwdzM3sawNTGxdF3vvMdffKTn/T7GGAVyPxPHos5pw4OBAjUaXXR\nDnMmaQgUuI8rQdwcvfjii14Rgjybt2zWALeBIpYL5LuwwDydKMT+qSnpynZriuQmp1xApa4tJaUr\nLTNdWakd/G4kOEWMxi1KGTFIpUWM/fSaoCv9ZLysxxCcYBXy5JNP+jUbY2ezaNZwtsYCx7Dm6ArK\noUxAICAQELg8EWCOiQXHA3AKOj64tNgZ82Pr7RBdFASC4OCiwBwaCQgEBAIClwcCEIYQ30YwM+lz\nDdEIwZ2RHtPkIw2GOqb9bE4IwwDNNRjuuCZAqABhzkFZAnVzwFCHeY4mPgeMAZgObHaMGx/Tsodo\nResNBj7EKwdtcpiVAX2iLxdC0FLW+mjjpr+kUTem+vT5c5/7nCewn3jiCd/erFmzfP/IB07WB+sP\nZZoTnRDBEfdJTU4I45iKjNsOf9/lYSwc1FHihAnssYA1ApguWbJEO52m5ciRI72QASYMmFtb9DOE\ngEBAoH0EmuqOqfLgKj353Eat27hbTZUb9fbqXa5ApZ559CFtWTdVxSNm644bp2hYdoOOl21W2c6R\n2lY7RHUNLWqoO6yK3av02Itb3bdtqxort7jye1z5Bj39hwe0de1cDS2eptuvH6PRw3LO+Ba036tw\nJyDQdxFwM7kXFsB0RvjPHMWcT4z1XHl5uT7zmc94BQKUCJizsOLLzc3186rNucyVHMy7NpdzbXMv\nDG3cFcLQRlnhvvvuE3siTJw40VvwmaAhWpbyXFtadK60esnDnMt8iuAegT35WI8gROA+FgmE6Nze\n6SfmhAXpbodH9pU8Vr5XJyu9yCBSjRNAHpMOR1I6dJpVoyG1zu2DWzN0JVCOAzzAlT2seHYEMGff\nJQQqKEyAMViSF4yiePoC4U9AICAQEAgIBATaQCA6X0TP28gaki4CAkFwcBFADk0EBAICAYHLAQEj\nCiEoo4Qi5xD2HAgCTJsPVzowDhAWQHzjvximAceJEyd8GgwEb1lw/Jiqq6q9EAC3RxwIBHDfg4CA\nTY8h1LEu4NzasbYg8k14wLlnNDjiPsn1rTsWI0YU85ypz65h7tMn2qbNV1991WtScg6TYcGCBZ4Z\nQn+tLDHlOShveIIjwhUTHBCDH+2BBZYaCE7ADn/L5n8ZpgnCCywPaI89EMANoh4sYHLYs/OdCH8C\nAgEBhwBMNSeobKhW1dFtWvbKn/SjB55TQl6JSvJTnJuTLL368x9q9RV3qWh+keZfOVIFKSe0c+tq\nlR3KV8IAtl2jvPNHfmSTli55XP/+mxeUXlSqoVnJmjwlTYv/379p3fVNGjprkObPGaHRAfeAQD9H\ngHmPeQv3NljKwXDGrSAWc0899ZTY9wih+rXXXutdEiEwYB60OYp5kTnLz+FuTmRetPVGdN5FoQAl\nBKwXHnzwQd1yyy263lkgTnXzJHMywdYJlKfO6FxoddGuBdLIy7qCA7eBjAXteuZmxvav//qvvl7G\ngNCDNqJ1WF3nj2k3SwMHD9Gcz05V0/ZklW2rV26q24w4Xn5w/sp8jgQ2ZGnYpdxxRU5I6dyopXTQ\nUqGN+s1FERj/5Cc/8VagKChgAYoLqKlTp/p1T/T5dA2HNhoPSQGBgEBAICAQEAgIXFQEguDgosId\nGgsIBAQCAv0fAYhDI7ohmiEcIfKNWU6a7UlAbAx9LAVKSko8IQ4BDmMc4tS024gJVjca+MnO16HV\nTb0mICCNa0uzc4h9mAP0iX7a0R1PxY/bWQcQE+gv5whG6BfMBdqFaf/cc8/5jaJxWwQzH5cHUeaI\n1ZHoxggD0+qyvoMLB+MxrMCLfFhUYMXB5oS4eGAvCdxBoRX57LPPep/DV199tRYuXOjzocVJPRas\nLbsOcUDgUiDAe3hpQ+x3nJw1VEWT79Hf/c/b9IW/rXW/aX7bp3uWlOKEghk5GjzwmA5v36Q/fXuV\nsr94v953+2zlOgFBWuZIjZhxv771nbv15W/UiW0MTpd3QtY0x8Bz5QflZsQqbf1+nG4hnAUE+gcC\n/KZRBmBOWuKs4dik+LHHHvObFE+fPl0//elPvQIAygAItpm3KWNM/eRk1hExJj9zKemsB2xNAEqc\nM6++8cYbevzxx/XII4/oz/7sz7xAgjmR+ZFy1M28F18PdTD/2hzMtQXSqJ/yzOkIDfDhf9ttt7l6\nUlx7j/n0FStW6OGHH9Z73/ves+Z2q+t8ccy1YJaGjLpK9/7XR3RHbbNqnAVT7Kt0vtLnuu/wdN+c\nNPfNGZKf5XZKYLznyn/mPVsfsK7BPdHSpUv9c+SZIeTBqgNFBdZzYMRazJ5TW5ieWXu4CggEBAIC\nAYGAQECgNyIQBAe98amEPgUEAgIBgT6OgBGIRtATcxiRDsEO4Q7hDeMbYp7YGOKmVQ8MEKoc0RAl\n4K1OiFMTIhBbG8Sp7jqZwzEbrE/UYf2M1n0h565GlJR9O1Z31GqAPQm4xooC1wwQ3QgS6G9bPpFj\nBH2Mqmd84GBYGjFODF4mQOAabAm0xfgRziAgQMPz8OHD2rZtm+8j51hqcKAdaX25EAxC2YBAdyDA\ne26/e4u7o95O15HgmIvp+Ro+Iv8cRZtVfXCDyg/u0qFJzk3HlLGaP6VQ6Sl8D9KUkpmmESMLzlGe\nW6e/c2d+7dovBi58Zyz2tcR9K9svHe4EBHoeAd7NiooKP/dgTXjgwAHt2LFDmzdv9vPUxz/+cT/3\nsAfSpImTvMUg8xXlbK6zOZ65jPnN5r7oXM5IKHPw4EFf/8svv+zbvOmmm/xeQ2yojKUidfk1gauL\neZdrfkPUda5gvzPyJbuN0G2NgbXfhAnjvcueN99c7udcXAWy3xKa98yptkHwuepv+16iUtOdULHY\nHW1nuOipYIzQAJxfe+01rVq1yvcBCw8wnjdvnl9PmGAGnHhe4McRQkAgIBAQCAgEBAICfQ+BIDjo\ne88s9DggEBAICPQJBIxINIKRGCIdQhKiEmY3ggNjehvj22KECDC+jfFugzZmQYyAP+2qwJgAxNFz\nYzpYuWi/rM7uim2sENcEGBSk0TbENowL9mJAUIJrhq997Ws6cfKEFyTcfffd3uUQeTmiwfpMmrVB\nHghywygeR67ph/mHxrczjJstW7Z4y4Mf/ehHnolz1fyr9K7b36Xrr7/eE/64kLK649uN9imcBwS6\nHQHHV+KdJuDKBP/nMBF5xy91sN/0Wf1wv+8Wt3n5vlUrtGPbdmXd9EGNGjlCI9OrdNJtiFzVyitr\ntzwVujq6ylLjtwrTjgOcDL+z+hkSAgI9iIC938R2MAfhhnDdunXeTd8vf/lLbdy40ffinnvu0Y03\n3qgrZl2h7AHZfs6mnM19tlawmPfaDptTbTjWHt8MtOBffvklfe97/6gvfOELvg0Y2mjAUx4teNYf\nrBG4pj1r0+prLz4998YEB9TDXD58+AjvAhDrQRjpCErYywgrQwJul8gX3+/22jkzHTzPTOmuq+j8\n3pE6+b40OT9Jhw4e8jj/7Gc/8woQuGxircPaBhdNrCG4Bh+eH/h2tq2O9CfkCQgEBAICAYH2EbC5\nEXraQnvfYtJP3+PcSrQdn87b9v2Q2v8QCIKD/vdMw4gCAgGBgECvQSC6sIBIh/AkDUKSa4h30mAw\nmLVB1PLAFj3E0RCtwwQDFlOvEaucW17ri8XR+rr73Nqk3mjfjUGBhj+bB/793/+9348AlwpggbYe\nxLeVie+rXcNmbEk4raFs7dnYwRJM7eCaOtn/AS1I2r/9jtt1YP8B7zYCH9O4jSgtLfXMDvqG+ySs\nFEIICFwsBBITEr2gC0ucf/7nf/bvIxq99nu4WP3obDstLc06cXC9jh7eqpe2TFXl5iF6bNhA923r\nDtci5+4Nv32+mQgi2b/k/e9/vxdAnrtUuBsQ6F4EbG6iVvbZeeedd7yLPIQGbJiLYIt9dj75yU+q\npKTEuyLCvY0JDaLztwn+mc/sYO60gzZoz74LpCMUX758ud8IGeHEV7/6Ve+eaFTJKC98hJFtR1eE\nBrRJsLmW/lIfc6vtc4BrQKz6sOjD0mCJc8dUWVnp51HmddtbIVZTR/+en4HT0ZouNB/fGVxNLXlp\niX7961+fEsRgYfGVr3zFbzyNgAaBQRAaXCjaoXxAICAQEOg6AsyPfK9RwGFegta2OZSYuTU6J3LO\ndxtlHQTszHEhBASiCIQ3IopGOA8IBAQCAgGBHkHAmAosVgi2aGFhw2LGCHDOIcSJObhvzAGLqcsO\nqycaG2FveYgJFvuLi/DH+sHiK74vLNjwA8wiDWIctwbse5CaEnMrBIOBhRtjbrPfbkgOBT8K6jKc\nDAcwpF1i6udAiIDfaDQfERzAyDky6oiys7J9XlwnsakyTACsI1hs4loJKwmYARxt9uUiYBma6N8I\n2HvFO8ummry3MPdI573tC2HgsBnKHT5L42e731yjO+obXf8vTs/5BiB0RNjHBukwLQmG68XpRWjl\nckSAuYffK5YFMMmZN3BHhJ9/hAe4JGLT3JKSEm/Rxl4GnEeDzVv85u3gnSadd9hizqPvNOd8H3C5\nxya9L7zwgp+/0IDHwq7UCcIRfvNdMaZIVGgQrSvan/Od0x/GTV2sU5jHcfVHOu3CeFm7dq23PkBo\nQj/AiDEhCKU/fSkwRoQjPNdVq1bqlVde8esV3CuiiADe7KvEOI3plJqWeuq59aWxhr4GBAICAYG+\njoDNy3yz2VMIAT50IHMP8x6xzYvQmsyPxHy/oRH9kZGpRLdvH/mYuzhsfmbOIz/5mPdCuDwQ6Fsr\nl8vjmYRRBgQCAgGBfouAEeoWs7ixRQeLk6iwgHsEi6OgWHliO6jHzi2v5bPrix3Tvo3P+mZ9YoFW\nXFysG264QWhefve739XRo0e1fcd2ffSjH/Wa19ZfK2PXFls6seHEQo82wRNmBTGLPc6jQgQWgbgU\nuPa6a3Xl3Cs904fFJdreX/ziF30Tt9xyi9dghinAweLS2oq2bf0JcUDgQhCAGMHdB0xwNk4n2Ht2\nIY0rEokAAEAASURBVPVejLL2+7O2Lna/+XbyO/eEnPtthxAQ6AkE7D0n5h1nXkFYsGnTJi1xGvYw\nlRcvXuybZqPcD3/4w5o5c6bfOJf8Ni/ZHGXzE++uMSe4x0F+i+PHwvvOfQQWjz76qF5f9roe+MUD\n+ta3vuWt+UqccAJBOfUbY4Rz2rD64+vsyDVt+rG7Xc6pj3PmcvqDcP3mm2/28/kzzzzjLQzI8/Wv\nf12f/exnT1ldIMww/DrS5qXKQx8JCGf2H9ivl5a8pE984hNeoQAhAXtVsIcEx6hRIz3Otqk1ShCM\nvb3nd6nG1HfavUhS574DSD/saXjG/fChXvIh2Xcbeg/rN5TSfvWrX3karyudQyEFZTM7oFv5/uMC\nkINvfvQ7zxzJEUL/QyAIDvrfMw0jCggEBAICfQaB6OKCcxYfEOAEW/y0Nxgr217cXrlLkc64CMZo\nsLHRd5j3uBjBhQP7D+A2qLh4mKZPjzHryUN+G2d7/bf7bsmmhP+fve8A7KLI/v+kFwgJSeglhYTe\nEaR3qVYUG+rpYblTz5/du7Nw53l6dj3179kLWFGxVxRUpChNkd5L6CQkpNf/+8zmJZsQQhJSvgkz\nsJn97k797O57M+/Ne+NTnId1U1jiViJQEKAHy6PAlgJHBq6I7Nevn9nskeatdP+wfft2Y40QLcIY\nDho7dOhg8pgM9o9FoBoRoHKKBycjNlgELAKehYDyGfrxp3sgrmbctm0bduzYYTbMpZXa7bffbhQF\nFDRwJX6LFi2MFQx5uwruyQv1UIUBf7N8HsoztT5FQXkn79NKji72yKNSj6QadzlUcHMFPPlZQAD3\nM3DoCcvWukuXqWVXNDbtg1gdeBeYPpB/kr+Sp3Ij5E6dOhkMqEShCzHWzXZ6i7KBClHuA0ArDIaK\n8PaKtqu607GfVAoR58WLF8veET8gQsYrfPZ0e8h9KjhWIN5NmoQWWxsI/SbWJ4pzdfenfpVX0j1n\n/Wq7bW3FEOAztgLWimFlU1UGAfIV8ludT5Nep6amFlnJ8bryUi1X54qk3W7eTAt0Wi7QBaHbgoGW\n8eTxLJvnVDBwTz1aqTN4Mm/TPtu4cghYxUHl8LKpLQIWAYuARaCaESg9uVSBQUWrKZ2/ovlqK522\nj/3Sc3fdvM6J9/jx481gbfbs2Zg9+z3xC33ICCE4INOV/u585Z1rPSoo4QCOA0FVHqiQQy0QWBbb\nES2KAQo0eJ9KDLqboMCAghkKECZNmmQsDyggoZUEhbsU0LBsfW5ad3nts/csAuUhUHpCU15ae68k\nAvb7K4mH/XViCIizQKqijQCCQm8KEShA4EpGWhnQzR55BIXndDM2YMAAUXr3BN3YkG9RQKHvpLo5\nUKEEY+VRTOPmkZqnrNaTb9EtEjdCfvvtt7F792707dsXEyZMMPWSJ7EuKg1obaD1aB1llVnZa+6y\n2HfSLB7knVSejBw50lhDUFjDgwoEHgkJu43bH7aJAha2z93vyrajJtKzH8SY7gzXrFmDefPm4f33\n3zfKD44PmogrNK40HT16tNmTicoSjgXYF2Kh1iPlPcOaaLct0yJgEbAInOwIkH7n54vLX+FFpMtc\n7MXFaeRLDOTJeXm5QuO5P09WkSW68jB3zPT8TR7G/RJo4Ue3daUDrc7OOussw/tZF91lkhfY0LAQ\nsIqDhvU8bW8sAhYBi0C9R6ChTja1XxSUMPC3HhzIURA/bNgws4Jj5syZxt0D/SNPmzbN+C1XAYyW\nc7wHrekYc+CndbJ+CjcYc4JPJQCFBKpM4G+m5x4MVFqMGDHCbKxFn82//vorXn75Zbz66qtGQMTV\nhrzPVaW6Qpx5te7jtdHetwiUhYB9f8pCxV6zCNQ+AlQaMFBhQEUBlclcSb9y5UrDJzp37oy//OUv\nZrUhVx7SXQ9d9yifUyUBeY2e8x4PfucqNOd5ed+9m4dRgPH666/jl19+MQruK6+6Ep07dTa8k3VT\nYUGhBWNVGmg91Ymgtp99YV1sI/koA/k1Xf3RpQP5JQN5PJUHVLzMF7dOdONEJYvuSWIS1dEfN99m\nH2ht+MEHH5j2LvhxAXx8fczKUlqWXHXVVWYvB44R+MypqOFB7EsrDcp7pnXUVVutRcAiYBFosAiQ\nlufny5xPeGp8fLzhO7Ryy8jIMPM90nflp+RTTvp8Yw1HPk+FMWOmp8KA/IqK+uTkZFnQdtDs3+MG\njwpwLjR7/PHHzTjg3HPPNS5HqUBw8xV3HntePxGwioP6+dxsqy0CFgGLgEWgHiKgk2gVqnBQpQfv\n0eyTE+/hw4cb9wAU0nTs2NEII+j+oKorOFg266HwRAdyPOegkTHbw8EkFQi+Pr6yuauziRaVAbzP\ngSHTUChEU9WEhASzISXbx3xcXUoTVbafaSlAsMEiYBGwCFgE6i8CXF3IjYcpRGZMt0S0NKAggUp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IqO+bJh7z/+8Q9MmjTJuCjiRs2sl/sX6Kp3bSfbxnZUV1u0b9UZa/v0WTl9cXg7caZwnnyd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\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gdKxIwjSJB/0dNCGCjDYSMx577DHQPA+l4W+99ValaUBmAcvCs9Y6GA5MA92HyTCheTOO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\nQQtvbW2Bk5g2cnH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ajqgJCcmi8iqJiyQ3ifevvPiMOhjhuz/5E779wD0I9/MQqXAxKUPV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7Ft9IGhdn7aBIsLPMzN7du369VXX9Vvf/tbfyjyl7/8ZW+eCO1qGKLmg9Cg5bqiHRuesetT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oLGA9cKUxyUPeR8JNiWkSbzyvkb/7xkDDp7/yqxixPtieeaztmuQnhTCtbWK+qNXrA4Ha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\nGO85JRSSSzw4rrdujcr8QQIkQAIkQAJ3kAANB3cQNrsiARIgARIgARIgARI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+ "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": { + "image/png": { + "width": 800 + } + }, + "output_type": "execute_result" + } + ], + "source": [ + "Image(filename='./images/bonus_softmax_1.png', width=800) " + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -989,7 +997,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 25, "metadata": { "collapsed": true }, @@ -1003,16 +1011,14 @@ }, { "cell_type": "code", - "execution_count": 37, - "metadata": { - "collapsed": false - }, + "execution_count": 26, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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Jb5aZLQBygbnxDkqkI3viiScoLS1l4sSJjB6dko8oirSqpnamuAJ43N1L3H1B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\nIiIp7f8BNM/UAollYmAAAAAASUVORK5CYII=\n", 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x47399tskJycze/Zspk6dWiw+d+5cEhMTmTlzJjNnziwWX7hwIVFRUbz66qvM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\n8HDCwsIIDQ0lMTGRefPmAfD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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -1056,10 +1062,8 @@ }, { "cell_type": "code", - "execution_count": 6, - "metadata": { - "collapsed": false - }, + "execution_count": 27, + "metadata": {}, "outputs": [ { "data": { @@ -1068,7 +1072,7 @@ "" ] }, - "execution_count": 6, + "execution_count": 27, "metadata": { "image/png": { "width": 700 @@ -1096,6 +1100,24 @@ "# Training neural networks efficiently using Keras" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "--- \n", + "**Note about installing Keras**\n", + "\n", + "As a [kind reader pointed out](http://www.mostafaelzoghbi.com/2017/04/how-to-install-keras-on-windows-10-64.html), Keras can now be installed from conda-forge, which is a community-driven effort to make packages available to the conda manager -- if you have troubles installing Keras via `pip` (`pip install keras`). To install Keras from conda-forge, you need to specify the respective conda channel as shown below:\n", + "\n", + "```bash\n", + "conda install -c conda-forge keras=2.0.2\n", + "```\n", + "\n", + "(End of note.)\n", + "\n", + "---" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -1121,7 +1143,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 28, "metadata": { "collapsed": true }, @@ -1155,10 +1177,8 @@ }, { "cell_type": "code", - "execution_count": 34, - "metadata": { - "collapsed": false - }, + "execution_count": 29, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1169,16 +1189,14 @@ } ], "source": [ - "X_train, y_train = load_mnist('mnist', kind='train')\n", + "X_train, y_train = load_mnist('./mnist', kind='train')\n", "print('Rows: %d, columns: %d' % (X_train.shape[0], X_train.shape[1]))" ] }, { "cell_type": "code", - "execution_count": 35, - "metadata": { - "collapsed": false - }, + "execution_count": 30, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1211,9 +1229,7 @@ }, { "cell_type": "markdown", - "metadata": { - "collapsed": false - }, + "metadata": {}, "source": [ "In order to run the following code via GPU, you can execute the Python script that was placed in this directory via\n", "\n", @@ -1222,9 +1238,9 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 31, "metadata": { - "collapsed": false + "collapsed": true }, "outputs": [], "source": [ @@ -1244,10 +1260,8 @@ }, { "cell_type": "code", - "execution_count": 38, - "metadata": { - "collapsed": false - }, + "execution_count": 32, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -1273,125 +1287,123 @@ }, { "cell_type": "code", - "execution_count": 49, - "metadata": { - "collapsed": false - }, + "execution_count": 33, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Train on 54000 samples, validate on 6000 samples\n", - "Epoch 0\n", - "54000/54000 [==============================] - 1s - loss: 2.2290 - acc: 0.3592 - val_loss: 2.1094 - val_acc: 0.5342\n", - "Epoch 1\n", - "54000/54000 [==============================] - 1s - loss: 1.8850 - acc: 0.5279 - val_loss: 1.6098 - val_acc: 0.5617\n", - "Epoch 2\n", - "54000/54000 [==============================] - 1s - loss: 1.3903 - acc: 0.5884 - val_loss: 1.1666 - val_acc: 0.6707\n", - "Epoch 3\n", - "54000/54000 [==============================] - 1s - loss: 1.0592 - acc: 0.6936 - val_loss: 0.8961 - val_acc: 0.7615\n", - "Epoch 4\n", - "54000/54000 [==============================] - 1s - loss: 0.8528 - acc: 0.7666 - val_loss: 0.7288 - val_acc: 0.8290\n", - "Epoch 5\n", - "54000/54000 [==============================] - 1s - loss: 0.7187 - acc: 0.8191 - val_loss: 0.6122 - val_acc: 0.8603\n", - "Epoch 6\n", - "54000/54000 [==============================] - 1s - loss: 0.6278 - acc: 0.8426 - val_loss: 0.5347 - val_acc: 0.8762\n", - "Epoch 7\n", - "54000/54000 [==============================] - 1s - loss: 0.5592 - acc: 0.8621 - val_loss: 0.4707 - val_acc: 0.8920\n", - "Epoch 8\n", - "54000/54000 [==============================] - 1s - loss: 0.4978 - acc: 0.8751 - val_loss: 0.4288 - val_acc: 0.9033\n", - "Epoch 9\n", - "54000/54000 [==============================] - 1s - loss: 0.4583 - acc: 0.8847 - val_loss: 0.3935 - val_acc: 0.9035\n", - "Epoch 10\n", - "54000/54000 [==============================] - 1s - loss: 0.4213 - acc: 0.8911 - val_loss: 0.3553 - val_acc: 0.9088\n", - "Epoch 11\n", - "54000/54000 [==============================] - 1s - loss: 0.3972 - acc: 0.8955 - val_loss: 0.3405 - val_acc: 0.9083\n", - "Epoch 12\n", - "54000/54000 [==============================] - 1s - loss: 0.3740 - acc: 0.9022 - val_loss: 0.3251 - val_acc: 0.9170\n", - "Epoch 13\n", - "54000/54000 [==============================] - 1s - loss: 0.3611 - acc: 0.9030 - val_loss: 0.3032 - val_acc: 0.9183\n", - "Epoch 14\n", - "54000/54000 [==============================] - 1s - loss: 0.3479 - acc: 0.9064 - val_loss: 0.2972 - val_acc: 0.9248\n", - "Epoch 15\n", - "54000/54000 [==============================] - 1s - loss: 0.3309 - acc: 0.9099 - val_loss: 0.2778 - val_acc: 0.9250\n", - "Epoch 16\n", - "54000/54000 [==============================] - 1s - loss: 0.3264 - acc: 0.9103 - val_loss: 0.2838 - val_acc: 0.9208\n", - "Epoch 17\n", - "54000/54000 [==============================] - 1s - loss: 0.3136 - acc: 0.9136 - val_loss: 0.2689 - val_acc: 0.9223\n", - "Epoch 18\n", - "54000/54000 [==============================] - 1s - loss: 0.3031 - acc: 0.9156 - val_loss: 0.2634 - val_acc: 0.9313\n", - "Epoch 19\n", - "54000/54000 [==============================] - 1s - loss: 0.2988 - acc: 0.9169 - val_loss: 0.2579 - val_acc: 0.9288\n", - "Epoch 20\n", - "54000/54000 [==============================] - 1s - loss: 0.2909 - acc: 0.9180 - val_loss: 0.2494 - val_acc: 0.9310\n", - "Epoch 21\n", - "54000/54000 [==============================] - 1s - loss: 0.2848 - acc: 0.9202 - val_loss: 0.2478 - val_acc: 0.9307\n", - "Epoch 22\n", - "54000/54000 [==============================] - 1s - loss: 0.2804 - acc: 0.9194 - val_loss: 0.2423 - val_acc: 0.9343\n", - "Epoch 23\n", - "54000/54000 [==============================] - 1s - loss: 0.2728 - acc: 0.9235 - val_loss: 0.2387 - val_acc: 0.9327\n", - "Epoch 24\n", - "54000/54000 [==============================] - 1s - loss: 0.2673 - acc: 0.9241 - val_loss: 0.2265 - val_acc: 0.9385\n", - "Epoch 25\n", - "54000/54000 [==============================] - 1s - loss: 0.2611 - acc: 0.9253 - val_loss: 0.2270 - val_acc: 0.9347\n", - "Epoch 26\n", - "54000/54000 [==============================] - 1s - loss: 0.2676 - acc: 0.9225 - val_loss: 0.2210 - val_acc: 0.9367\n", - "Epoch 27\n", - "54000/54000 [==============================] - 1s - loss: 0.2528 - acc: 0.9261 - val_loss: 0.2241 - val_acc: 0.9373\n", - "Epoch 28\n", - "54000/54000 [==============================] - 1s - loss: 0.2511 - acc: 0.9264 - val_loss: 0.2170 - val_acc: 0.9403\n", - "Epoch 29\n", - "54000/54000 [==============================] - 1s - loss: 0.2433 - acc: 0.9293 - val_loss: 0.2165 - val_acc: 0.9412\n", - "Epoch 30\n", - "54000/54000 [==============================] - 1s - loss: 0.2465 - acc: 0.9279 - val_loss: 0.2135 - val_acc: 0.9367\n", - "Epoch 31\n", - "54000/54000 [==============================] - 1s - loss: 0.2383 - acc: 0.9306 - val_loss: 0.2138 - val_acc: 0.9427\n", - "Epoch 32\n", - "54000/54000 [==============================] - 1s - loss: 0.2349 - acc: 0.9310 - val_loss: 0.2066 - val_acc: 0.9423\n", - "Epoch 33\n", - "54000/54000 [==============================] - 1s - loss: 0.2301 - acc: 0.9334 - val_loss: 0.2054 - val_acc: 0.9440\n", - "Epoch 34\n", - "54000/54000 [==============================] - 1s - loss: 0.2371 - acc: 0.9317 - val_loss: 0.1991 - val_acc: 0.9480\n", - "Epoch 35\n", - "54000/54000 [==============================] - 1s - loss: 0.2256 - acc: 0.9352 - val_loss: 0.1982 - val_acc: 0.9450\n", - "Epoch 36\n", - "54000/54000 [==============================] - 1s - loss: 0.2313 - acc: 0.9323 - val_loss: 0.2092 - val_acc: 0.9403\n", - "Epoch 37\n", - "54000/54000 [==============================] - 1s - loss: 0.2230 - acc: 0.9341 - val_loss: 0.1993 - val_acc: 0.9445\n", - "Epoch 38\n", - "54000/54000 [==============================] - 1s - loss: 0.2261 - acc: 0.9336 - val_loss: 0.1891 - val_acc: 0.9463\n", - "Epoch 39\n", - "54000/54000 [==============================] - 1s - loss: 0.2166 - acc: 0.9369 - val_loss: 0.1943 - val_acc: 0.9452\n", - "Epoch 40\n", - "54000/54000 [==============================] - 1s - loss: 0.2128 - acc: 0.9370 - val_loss: 0.1952 - val_acc: 0.9435\n", - "Epoch 41\n", - "54000/54000 [==============================] - 1s - loss: 0.2200 - acc: 0.9351 - val_loss: 0.1918 - val_acc: 0.9468\n", - "Epoch 42\n", - "54000/54000 [==============================] - 2s - loss: 0.2107 - acc: 0.9383 - val_loss: 0.1831 - val_acc: 0.9483\n", - "Epoch 43\n", - "54000/54000 [==============================] - 1s - loss: 0.2020 - acc: 0.9411 - val_loss: 0.1906 - val_acc: 0.9443\n", - "Epoch 44\n", - "54000/54000 [==============================] - 1s - loss: 0.2082 - acc: 0.9388 - val_loss: 0.1838 - val_acc: 0.9457\n", - "Epoch 45\n", - "54000/54000 [==============================] - 1s - loss: 0.2048 - acc: 0.9402 - val_loss: 0.1817 - val_acc: 0.9488\n", - "Epoch 46\n", - "54000/54000 [==============================] - 1s - loss: 0.2012 - acc: 0.9417 - val_loss: 0.1876 - val_acc: 0.9480\n", - "Epoch 47\n", - "54000/54000 [==============================] - 1s - loss: 0.1996 - acc: 0.9423 - val_loss: 0.1792 - val_acc: 0.9502\n", - "Epoch 48\n", - "54000/54000 [==============================] - 1s - loss: 0.1921 - acc: 0.9430 - val_loss: 0.1791 - val_acc: 0.9505\n", - "Epoch 49\n", - "54000/54000 [==============================] - 1s - loss: 0.1907 - acc: 0.9432 - val_loss: 0.1749 - val_acc: 0.9482\n" + "Epoch 1/50\n", + "54000/54000 [==============================] - 0s - loss: 2.2244 - acc: 0.4249 - val_loss: 2.1019 - val_acc: 0.5712\n", + "Epoch 2/50\n", + "54000/54000 [==============================] - 0s - loss: 1.8746 - acc: 0.5297 - val_loss: 1.5900 - val_acc: 0.5878\n", + "Epoch 3/50\n", + "54000/54000 [==============================] - 0s - loss: 1.3850 - acc: 0.6134 - val_loss: 1.1486 - val_acc: 0.7050\n", + "Epoch 4/50\n", + "54000/54000 [==============================] - 0s - loss: 1.0424 - acc: 0.7195 - val_loss: 0.8696 - val_acc: 0.7933\n", + "Epoch 5/50\n", + "54000/54000 [==============================] - 0s - loss: 0.8236 - acc: 0.7928 - val_loss: 0.6872 - val_acc: 0.8498\n", + "Epoch 6/50\n", + "54000/54000 [==============================] - 0s - loss: 0.6819 - acc: 0.8328 - val_loss: 0.5700 - val_acc: 0.8740\n", + "Epoch 7/50\n", + "54000/54000 [==============================] - 0s - loss: 0.5867 - acc: 0.8578 - val_loss: 0.5052 - val_acc: 0.8860\n", + "Epoch 8/50\n", + "54000/54000 [==============================] - 0s - loss: 0.5203 - acc: 0.8702 - val_loss: 0.4494 - val_acc: 0.8937\n", + "Epoch 9/50\n", + "54000/54000 [==============================] - 0s - loss: 0.4751 - acc: 0.8822 - val_loss: 0.4112 - val_acc: 0.9020\n", + "Epoch 10/50\n", + "54000/54000 [==============================] - 0s - loss: 0.4382 - acc: 0.8884 - val_loss: 0.3725 - val_acc: 0.9122\n", + "Epoch 11/50\n", + "54000/54000 [==============================] - 0s - loss: 0.4086 - acc: 0.8953 - val_loss: 0.3575 - val_acc: 0.9130\n", + "Epoch 12/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3889 - acc: 0.8981 - val_loss: 0.3393 - val_acc: 0.9118\n", + "Epoch 13/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3724 - acc: 0.9022 - val_loss: 0.3082 - val_acc: 0.9207\n", + "Epoch 14/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3490 - acc: 0.9082 - val_loss: 0.3083 - val_acc: 0.9202\n", + "Epoch 15/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3361 - acc: 0.9095 - val_loss: 0.2950 - val_acc: 0.9200\n", + "Epoch 16/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3279 - acc: 0.9108 - val_loss: 0.2829 - val_acc: 0.9262\n", + "Epoch 17/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3210 - acc: 0.9125 - val_loss: 0.2850 - val_acc: 0.9290\n", + "Epoch 18/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3067 - acc: 0.9166 - val_loss: 0.2699 - val_acc: 0.9275\n", + "Epoch 19/50\n", + "54000/54000 [==============================] - 0s - loss: 0.3006 - acc: 0.9173 - val_loss: 0.2502 - val_acc: 0.9380\n", + "Epoch 20/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2932 - acc: 0.9198 - val_loss: 0.2603 - val_acc: 0.9313\n", + "Epoch 21/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2859 - acc: 0.9201 - val_loss: 0.2457 - val_acc: 0.9325\n", + "Epoch 22/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2804 - acc: 0.9217 - val_loss: 0.2551 - val_acc: 0.9348\n", + "Epoch 23/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2735 - acc: 0.9233 - val_loss: 0.2457 - val_acc: 0.9342\n", + "Epoch 24/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2790 - acc: 0.9220 - val_loss: 0.2364 - val_acc: 0.9380\n", + "Epoch 25/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2747 - acc: 0.9227 - val_loss: 0.2361 - val_acc: 0.9345\n", + "Epoch 26/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2648 - acc: 0.9254 - val_loss: 0.2311 - val_acc: 0.9357\n", + "Epoch 27/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2627 - acc: 0.9249 - val_loss: 0.2319 - val_acc: 0.9343\n", + "Epoch 28/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2556 - acc: 0.9280 - val_loss: 0.2322 - val_acc: 0.9352\n", + "Epoch 29/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2599 - acc: 0.9264 - val_loss: 0.2249 - val_acc: 0.9410\n", + "Epoch 30/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2500 - acc: 0.9290 - val_loss: 0.2164 - val_acc: 0.9398\n", + "Epoch 31/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2460 - acc: 0.9291 - val_loss: 0.2132 - val_acc: 0.9425\n", + "Epoch 32/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2438 - acc: 0.9301 - val_loss: 0.2085 - val_acc: 0.9440\n", + "Epoch 33/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2366 - acc: 0.9323 - val_loss: 0.2104 - val_acc: 0.9437\n", + "Epoch 34/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2348 - acc: 0.9331 - val_loss: 0.2157 - val_acc: 0.9437\n", + "Epoch 35/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2333 - acc: 0.9323 - val_loss: 0.2109 - val_acc: 0.9405\n", + "Epoch 36/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2286 - acc: 0.9341 - val_loss: 0.2056 - val_acc: 0.9422\n", + "Epoch 37/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2261 - acc: 0.9353 - val_loss: 0.2144 - val_acc: 0.9448\n", + "Epoch 38/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2226 - acc: 0.9358 - val_loss: 0.2005 - val_acc: 0.9442\n", + "Epoch 39/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2192 - acc: 0.9365 - val_loss: 0.1990 - val_acc: 0.9450\n", + "Epoch 40/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2211 - acc: 0.9356 - val_loss: 0.2066 - val_acc: 0.9413\n", + "Epoch 41/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2237 - acc: 0.9356 - val_loss: 0.2165 - val_acc: 0.9380\n", + "Epoch 42/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2166 - acc: 0.9365 - val_loss: 0.1952 - val_acc: 0.9465\n", + "Epoch 43/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2109 - acc: 0.9392 - val_loss: 0.1905 - val_acc: 0.9492\n", + "Epoch 44/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2058 - acc: 0.9413 - val_loss: 0.1939 - val_acc: 0.9448\n", + "Epoch 45/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2075 - acc: 0.9398 - val_loss: 0.1934 - val_acc: 0.9448\n", + "Epoch 46/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2110 - acc: 0.9384 - val_loss: 0.1901 - val_acc: 0.9453\n", + "Epoch 47/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2048 - acc: 0.9406 - val_loss: 0.1833 - val_acc: 0.9493\n", + "Epoch 48/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2013 - acc: 0.9411 - val_loss: 0.1846 - val_acc: 0.9493\n", + "Epoch 49/50\n", + "54000/54000 [==============================] - 0s - loss: 0.2014 - acc: 0.9414 - val_loss: 0.1854 - val_acc: 0.9487\n", + "Epoch 50/50\n", + "54000/54000 [==============================] - 0s - loss: 0.1942 - acc: 0.9436 - val_loss: 0.1822 - val_acc: 0.9482\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 49, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -1405,87 +1417,57 @@ "\n", "model = Sequential()\n", "model.add(Dense(input_dim=X_train.shape[1], \n", - " output_dim=50, \n", - " init='uniform', \n", + " units=50, # formerly output_dim=50 in Keras < 2\n", + " kernel_initializer='uniform', # formerly init='uniform' in Keras < 2\n", " activation='tanh'))\n", "\n", "model.add(Dense(input_dim=50, \n", - " output_dim=50, \n", - " init='uniform', \n", + " units=50, \n", + " kernel_initializer='uniform', \n", " activation='tanh'))\n", "\n", "model.add(Dense(input_dim=50, \n", - " output_dim=y_train_ohe.shape[1], \n", - " init='uniform', \n", + " units=y_train_ohe.shape[1],\n", + " kernel_initializer='uniform', \n", " activation='softmax'))\n", "\n", "sgd = SGD(lr=0.001, decay=1e-7, momentum=.9)\n", - "model.compile(loss='categorical_crossentropy', optimizer=sgd)\n", + "model.compile(loss='categorical_crossentropy', \n", + " optimizer=sgd, \n", + " metrics=['accuracy'])\n", "\n", "model.fit(X_train, y_train_ohe, \n", - " nb_epoch=50, \n", + " epochs=50, # Keras 2: former nb_epoch has been renamed to epochs\n", " batch_size=300, \n", " verbose=1, \n", - " validation_split=0.1, \n", - " show_accuracy=True)" + " validation_split=0.1) \n", + " # removed former show_accuracy=True \n", + " # and added `metrics=['accuracy']` to the\n", + " # model.compile call for Keras >= 2" ] }, { "cell_type": "code", - "execution_count": 50, - "metadata": { - "collapsed": false - }, + "execution_count": 34, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "First 3 predictions: [5 0 4]\n" + "First 3 predictions: [5 0 4]\n", + "Training accuracy: 94.43%\n", + "Test accuracy: 93.90%\n" ] } ], "source": [ "y_train_pred = model.predict_classes(X_train, verbose=0)\n", - "print('First 3 predictions: ', y_train_pred[:3])" - ] - }, - { - "cell_type": "code", - "execution_count": 51, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Training accuracy: 94.51%\n" - ] - } - ], - "source": [ + "print('First 3 predictions: ', y_train_pred[:3])\n", + "\n", "train_acc = np.sum(y_train == y_train_pred, axis=0) / X_train.shape[0]\n", - "print('Training accuracy: %.2f%%' % (train_acc * 100))" - ] - }, - { - "cell_type": "code", - "execution_count": 53, - "metadata": { - "collapsed": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Test accuracy: 94.39%\n" - ] - } - ], - "source": [ + "print('Training accuracy: %.2f%%' % (train_acc * 100))\n", + "\n", "y_test_pred = model.predict_classes(X_test, verbose=0)\n", "test_acc = np.sum(y_test == y_test_pred, axis=0) / X_test.shape[0]\n", "print('Test accuracy: %.2f%%' % (test_acc * 100))" @@ -1517,24 +1499,25 @@ } ], "metadata": { + "anaconda-cloud": {}, "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.11" + "pygments_lexer": "ipython3", + "version": "3.6.1" } }, "nbformat": 4, - "nbformat_minor": 0 + "nbformat_minor": 1 } diff --git a/code/ch13/images/bonus_softmax_1.png b/code/ch13/images/bonus_softmax_1.png new file mode 100644 index 00000000..280c3045 Binary files /dev/null and b/code/ch13/images/bonus_softmax_1.png differ diff --git a/code/check_environment.ipynb b/code/check_environment.ipynb new file mode 100644 index 00000000..d5138da8 --- /dev/null +++ b/code/check_environment.ipynb @@ -0,0 +1,74 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Jupyter Notebook for Checking Python Package Requirements" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "from distutils.version import LooseVersion as Version\n", + "\n", + "\n", + "def get_packages(pkgs):\n", + " versions = []\n", + " for p in packages:\n", + " try:\n", + " imported = __import__(p)\n", + " try:\n", + " versions.append(imported.__version__)\n", + " except AttributeError:\n", + " try:\n", + " versions.append(imported.version)\n", + " except AttributeError:\n", + " try:\n", + " versions.append(imported.version_info)\n", + " except AttributeError:\n", + " versions.append('0.0')\n", + " except ImportError:\n", + " print('[FAIL]: %s is not installed' % p)\n", + " return versions\n", + " \n", + "packages = ['numpy', 'scipy', 'matplotlib', 'sklearn', 'pandas']\n", + "suggested_v = ['1.10', '0.17', '1.5.1', '0.17.1', '0.17.1']\n", + "versions = get_packages(packages)\n", + "\n", + "for p, v, s in zip(packages, versions, suggested_v):\n", + " if Version(v) < Version(s):\n", + " print('[FAIL] %s %s, please upgrade to >= %s' % (p, v, s))\n", + " else:\n", + " print('[OK] %s %s' % (p, v))" + ] + } + ], + "metadata": { + "anaconda-cloud": {}, + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.5.2" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} diff --git a/code/datasets/iris/iris.data b/code/datasets/iris/iris.data index 5c4316cd..396653cc 100644 --- a/code/datasets/iris/iris.data +++ b/code/datasets/iris/iris.data @@ -147,5 +147,4 @@ 6.3,2.5,5.0,1.9,Iris-virginica 6.5,3.0,5.2,2.0,Iris-virginica 6.2,3.4,5.4,2.3,Iris-virginica -5.9,3.0,5.1,1.8,Iris-virginica - +5.9,3.0,5.1,1.8,Iris-virginica \ No newline at end of file diff --git a/code/datasets/iris/iris.names.txt b/code/datasets/iris/iris.names.txt deleted file mode 100644 index 062b486d..00000000 --- a/code/datasets/iris/iris.names.txt +++ /dev/null @@ -1,69 +0,0 @@ -1. Title: Iris Plants Database - Updated Sept 21 by C.Blake - Added discrepency information - -2. Sources: - (a) Creator: R.A. Fisher - (b) Donor: Michael Marshall (MARSHALL%PLU@io.arc.nasa.gov) - (c) Date: July, 1988 - -3. Past Usage: - - Publications: too many to mention!!! Here are a few. - 1. Fisher,R.A. "The use of multiple measurements in taxonomic problems" - Annual Eugenics, 7, Part II, 179-188 (1936); also in "Contributions - to Mathematical Statistics" (John Wiley, NY, 1950). - 2. Duda,R.O., & Hart,P.E. (1973) Pattern Classification and Scene Analysis. - (Q327.D83) John Wiley & Sons. ISBN 0-471-22361-1. See page 218. - 3. Dasarathy, B.V. (1980) "Nosing Around the Neighborhood: A New System - Structure and Classification Rule for Recognition in Partially Exposed - Environments". IEEE Transactions on Pattern Analysis and Machine - Intelligence, Vol. PAMI-2, No. 1, 67-71. - -- Results: - -- very low misclassification rates (0% for the setosa class) - 4. Gates, G.W. (1972) "The Reduced Nearest Neighbor Rule". IEEE - Transactions on Information Theory, May 1972, 431-433. - -- Results: - -- very low misclassification rates again - 5. See also: 1988 MLC Proceedings, 54-64. Cheeseman et al's AUTOCLASS II - conceptual clustering system finds 3 classes in the data. - -4. Relevant Information: - --- This is perhaps the best known database to be found in the pattern - recognition literature. Fisher's paper is a classic in the field - and is referenced frequently to this day. (See Duda & Hart, for - example.) The data set contains 3 classes of 50 instances each, - where each class refers to a type of iris plant. One class is - linearly separable from the other 2; the latter are NOT linearly - separable from each other. - --- Predicted attribute: class of iris plant. - --- This is an exceedingly simple domain. - --- This data differs from the data presented in Fishers article - (identified by Steve Chadwick, spchadwick@espeedaz.net ) - The 35th sample should be: 4.9,3.1,1.5,0.2,"Iris-setosa" - where the error is in the fourth feature. - The 38th sample: 4.9,3.6,1.4,0.1,"Iris-setosa" - where the errors are in the second and third features. - -5. Number of Instances: 150 (50 in each of three classes) - -6. Number of Attributes: 4 numeric, predictive attributes and the class - -7. Attribute Information: - 1. sepal length in cm - 2. sepal width in cm - 3. petal length in cm - 4. petal width in cm - 5. class: - -- Iris Setosa - -- Iris Versicolour - -- Iris Virginica - -8. Missing Attribute Values: None - -Summary Statistics: - Min Max Mean SD Class Correlation - sepal length: 4.3 7.9 5.84 0.83 0.7826 - sepal width: 2.0 4.4 3.05 0.43 -0.4194 - petal length: 1.0 6.9 3.76 1.76 0.9490 (high!) - petal width: 0.1 2.5 1.20 0.76 0.9565 (high!) - -9. Class Distribution: 33.3% for each of 3 classes. diff --git a/code/optional-py-scripts/ch02.py b/code/optional-py-scripts/ch02.py index 218c28fc..3ce52fe8 100644 --- a/code/optional-py-scripts/ch02.py +++ b/code/optional-py-scripts/ch02.py @@ -30,7 +30,7 @@ class Perceptron(object): w_ : 1d-array Weights after fitting. errors_ : list - Number of misclassifications in every epoch. + Number of misclassifications (updates) in each epoch. """ def __init__(self, eta=0.01, n_iter=10): @@ -188,8 +188,8 @@ class AdalineGD(object): ----------- w_ : 1d-array Weights after fitting. - errors_ : list - Number of misclassifications in every epoch. + cost_ : list + Sum-of-squares cost function value in each epoch. """ def __init__(self, eta=0.01, n_iter=50): @@ -302,8 +302,9 @@ class AdalineSGD(object): ----------- w_ : 1d-array Weights after fitting. - errors_ : list - Number of misclassifications in every epoch. + cost_ : list + Sum-of-squares cost function value averaged over all + training samples in each epoch. shuffle : bool (default: True) Shuffles training data every epoch if True to prevent cycles. random_state : int (default: None) @@ -410,4 +411,4 @@ def predict(self, X): # plt.savefig('./adaline_5.png', dpi=300) plt.show() -ada.partial_fit(X_std[0, :], y[0]) +ada = ada.partial_fit(X_std[0, :], y[0]) diff --git a/code/optional-py-scripts/ch03.py b/code/optional-py-scripts/ch03.py index 66853790..3edd740c 100644 --- a/code/optional-py-scripts/ch03.py +++ b/code/optional-py-scripts/ch03.py @@ -12,7 +12,6 @@ import numpy as np from sklearn import datasets -from sklearn.cross_validation import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.metrics import accuracy_score from sklearn.linear_model import LogisticRegression @@ -21,9 +20,18 @@ from sklearn.tree import DecisionTreeClassifier from sklearn.ensemble import RandomForestClassifier from sklearn.neighbors import KNeighborsClassifier -from sklearn.tree import export_graphviz +# from sklearn.tree import export_graphviz from matplotlib.colors import ListedColormap import matplotlib.pyplot as plt +import warnings + +# for sklearn 0.18's alternative syntax +from distutils.version import LooseVersion as Version +from sklearn import __version__ as sklearn_version +if Version(sklearn_version) < '0.18': + from sklearn.grid_search import train_test_split +else: + from sklearn.model_selection import train_test_split ############################################################################# print(50 * '=') @@ -101,6 +109,7 @@ def plot_decision_regions(X, y, classifier, test_idx=None, resolution=0.02): marker='o', s=55, label='test set') + X_combined_std = np.vstack((X_train_std, X_test_std)) y_combined = np.hstack((y_train, y_test)) @@ -123,6 +132,7 @@ def plot_decision_regions(X, y, classifier, test_idx=None, resolution=0.02): def sigmoid(z): return 1.0 / (1.0 + np.exp(-z)) + z = np.arange(-7, 7, 0.1) phi_z = sigmoid(z) @@ -154,6 +164,7 @@ def cost_1(z): def cost_0(z): return - np.log(1 - sigmoid(z)) + z = np.arange(-10, 10, 0.1) phi_z = sigmoid(z) @@ -191,7 +202,8 @@ def cost_0(z): # plt.savefig('./figures/logistic_regression.png', dpi=300) plt.show() -print('Predicted probabilities', lr.predict_proba(X_test_std[0, :])) +print('Predicted probabilities', lr.predict_proba(X_test_std[0, :] + .reshape(1, -1))) ############################################################################# print(50 * '=') @@ -199,7 +211,7 @@ def cost_0(z): print(50 * '-') weights, params = [], [] -for c in np.arange(-5, 5): +for c in np.arange(-5.0, 5.0): lr = LogisticRegression(C=10**c, random_state=0) lr.fit(X_train_std, y_train) weights.append(lr.coef_[1]) @@ -323,6 +335,7 @@ def entropy(p): def error(p): return 1 - np.max([p, 1 - p]) + x = np.arange(0.0, 1.0, 0.01) ent = [entropy(p) if p != 0 else None for p in x] diff --git a/code/optional-py-scripts/ch04.py b/code/optional-py-scripts/ch04.py index 596f4cc7..68e75873 100644 --- a/code/optional-py-scripts/ch04.py +++ b/code/optional-py-scripts/ch04.py @@ -18,7 +18,6 @@ from sklearn.preprocessing import OneHotEncoder from sklearn.preprocessing import MinMaxScaler from sklearn.preprocessing import StandardScaler -from sklearn.cross_validation import train_test_split from sklearn.linear_model import LogisticRegression from sklearn.neighbors import KNeighborsClassifier from sklearn.ensemble import RandomForestClassifier @@ -27,6 +26,13 @@ from itertools import combinations import matplotlib.pyplot as plt +# for sklearn 0.18's alternative syntax +from distutils.version import LooseVersion as Version +from sklearn import __version__ as sklearn_version +if Version(sklearn_version) < '0.18': + from sklearn.grid_search import train_test_split +else: + from sklearn.model_selection import train_test_split ############################################################################# print(50 * '=') @@ -233,7 +239,7 @@ 'gray', 'indigo', 'orange'] weights, params = [], [] -for c in np.arange(-4, 6): +for c in np.arange(-4.0, 6.0): lr = LogisticRegression(penalty='l1', C=10**c, random_state=0) lr.fit(X_train_std, y_train) weights.append(lr.coef_[1]) @@ -382,5 +388,11 @@ def _calc_score(self, X_train, y_train, X_test, y_test, indices): # plt.savefig('./random_forest.png', dpi=300) plt.show() -X_selected = forest.transform(X_train, threshold=0.15) +if Version(sklearn_version) < '0.18': + X_selected = forest.transform(X_train, threshold=0.15) +else: + from sklearn.feature_selection import SelectFromModel + sfm = SelectFromModel(forest, threshold=0.15, prefit=True) + X_selected = sfm.transform(X_train) + X_selected.shape diff --git a/code/optional-py-scripts/ch05.py b/code/optional-py-scripts/ch05.py index be9c637a..215b0150 100644 --- a/code/optional-py-scripts/ch05.py +++ b/code/optional-py-scripts/ch05.py @@ -12,13 +12,12 @@ import pandas as pd import numpy as np -from sklearn.cross_validation import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.decomposition import PCA import matplotlib.pyplot as plt from matplotlib.colors import ListedColormap from sklearn.linear_model import LogisticRegression -from sklearn.lda import LDA +from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA from sklearn.datasets import make_moons from sklearn.datasets import make_circles from sklearn.decomposition import KernelPCA @@ -27,6 +26,17 @@ from scipy.linalg import eigh from matplotlib.ticker import FormatStrFormatter +# for sklearn 0.18's alternative syntax +from distutils.version import LooseVersion as Version +from sklearn import __version__ as sklearn_version +if Version(sklearn_version) < '0.18': + from sklearn.grid_search import train_test_split + from sklearn.lda import LDA +else: + from sklearn.model_selection import train_test_split + from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA + + ############################################################################# print(50 * '=') print('Section: Unsupervised dimensionality reduction' @@ -165,6 +175,7 @@ def plot_decision_regions(X, y, classifier, resolution=0.02): alpha=0.8, c=cmap(idx), marker=markers[idx], label=cl) + lr = LogisticRegression() lr = lr.fit(X_train_pca, y_train) @@ -270,7 +281,7 @@ def plot_decision_regions(X, y, classifier, resolution=0.02): plt.xlabel('Linear Discriminants') plt.ylim([-0.1, 1.1]) plt.legend(loc='best') -plt.tight_layout() +# plt.tight_layout() # plt.savefig('./figures/lda1.png', dpi=300) plt.show() @@ -586,6 +597,7 @@ def project_x(x_new, X, gamma, alphas, lambdas): k = np.exp(-gamma * pair_dist) return k.dot(alphas / lambdas) + # projection of the "new" datapoint x_reproj = project_x(x_new, X, gamma=15, alphas=alphas, lambdas=lambdas) print('Reprojection x_reproj:', x_reproj) diff --git a/code/optional-py-scripts/ch06.py b/code/optional-py-scripts/ch06.py index 54262b89..e7a7c79c 100644 --- a/code/optional-py-scripts/ch06.py +++ b/code/optional-py-scripts/ch06.py @@ -15,16 +15,10 @@ import pandas as pd import matplotlib.pyplot as plt from sklearn.preprocessing import LabelEncoder -from sklearn.cross_validation import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.decomposition import PCA from sklearn.linear_model import LogisticRegression from sklearn.pipeline import Pipeline -from sklearn.cross_validation import StratifiedKFold -from sklearn.cross_validation import cross_val_score -from sklearn.learning_curve import learning_curve -from sklearn.learning_curve import validation_curve -from sklearn.grid_search import GridSearchCV from sklearn.tree import DecisionTreeClassifier from sklearn.svm import SVC from sklearn.metrics import confusion_matrix @@ -38,6 +32,24 @@ from sklearn.metrics import accuracy_score from scipy import interp +# for sklearn 0.18's alternative syntax +from distutils.version import LooseVersion as Version +from sklearn import __version__ as sklearn_version +if Version(sklearn_version) < '0.18': + from sklearn.grid_search import train_test_split + from sklearn.cross_validation import StratifiedKFold + from sklearn.cross_validation import cross_val_score + from sklearn.learning_curve import learning_curve + from sklearn.learning_curve import validation_curve + from sklearn.grid_search import GridSearchCV +else: + from sklearn.model_selection import train_test_split + from sklearn.model_selection import StratifiedKFold + from sklearn.model_selection import cross_val_score + from sklearn.model_selection import learning_curve + from sklearn.model_selection import validation_curve + from sklearn.model_selection import GridSearchCV + ############################################################################# print(50 * '=') print('Section: Loading the Breast Cancer Wisconsin dataset') @@ -83,31 +95,39 @@ print('Section: K-fold cross-validation') print(50 * '-') -kfold = StratifiedKFold(y=y_train, - n_folds=10, - random_state=1) +if Version(sklearn_version) < '0.18': + kfold = StratifiedKFold(y=y_train, + n_folds=10, + random_state=1) +else: + kfold = StratifiedKFold(n_splits=10, + random_state=1).split(X_train, y_train) scores = [] for k, (train, test) in enumerate(kfold): pipe_lr.fit(X_train[train], y_train[train]) score = pipe_lr.score(X_train[test], y_train[test]) scores.append(score) - print('Fold: %s, Class dist.: %s, Acc: %.3f' % (k+1, + print('Fold: %s, Class dist.: %s, Acc: %.3f' % (k + 1, np.bincount(y_train[train]), score)) print('\nCV accuracy: %.3f +/- %.3f' % (np.mean(scores), np.std(scores))) print('Using StratifiedKFold') -kfold = StratifiedKFold(y=y_train, - n_folds=10, - random_state=1) +if Version(sklearn_version) < '0.18': + kfold = StratifiedKFold(y=y_train, + n_folds=10, + random_state=1) +else: + kfold = StratifiedKFold(n_splits=10, + random_state=1).split(X_train, y_train) scores = [] for k, (train, test) in enumerate(kfold): pipe_lr.fit(X_train[train], y_train[train]) score = pipe_lr.score(X_train[test], y_train[test]) scores.append(score) - print('Fold: %s, Class dist.: %s, Acc: %.3f' % (k+1, + print('Fold: %s, Class dist.: %s, Acc: %.3f' % (k + 1, np.bincount(y_train[train]), score)) print('\nCV accuracy: %.3f +/- %.3f' % (np.mean(scores), np.std(scores))) @@ -134,12 +154,12 @@ ('clf', LogisticRegression(penalty='l2', random_state=0))]) train_sizes, train_scores, test_scores =\ - learning_curve(estimator=pipe_lr, - X=X_train, - y=y_train, - train_sizes=np.linspace(0.1, 1.0, 10), - cv=10, - n_jobs=1) + learning_curve(estimator=pipe_lr, + X=X_train, + y=y_train, + train_sizes=np.linspace(0.1, 1.0, 10), + cv=10, + n_jobs=1) train_mean = np.mean(train_scores, axis=1) train_std = np.std(train_scores, axis=1) @@ -182,12 +202,12 @@ param_range = [0.001, 0.01, 0.1, 1.0, 10.0, 100.0] train_scores, test_scores = validation_curve( - estimator=pipe_lr, - X=X_train, - y=y_train, - param_name='clf__C', - param_range=param_range, - cv=10) + estimator=pipe_lr, + X=X_train, + y=y_train, + param_name='clf__C', + param_range=param_range, + cv=10) train_mean = np.mean(train_scores, axis=1) train_std = np.std(train_scores, axis=1) @@ -345,7 +365,14 @@ X_train2 = X_train[:, [4, 14]] -cv = StratifiedKFold(y_train, n_folds=3, random_state=1) +if Version(sklearn_version) < '0.18': + cv = StratifiedKFold(y_train, + n_folds=3, + random_state=1) + +else: + cv = list(StratifiedKFold(n_splits=3, + random_state=1).split(X_train, y_train)) fig = plt.figure(figsize=(7, 5)) @@ -367,7 +394,7 @@ tpr, lw=1, label='ROC fold %d (area = %0.2f)' - % (i+1, roc_auc)) + % (i + 1, roc_auc)) plt.plot([0, 1], [0, 1], diff --git a/code/optional-py-scripts/ch07.py b/code/optional-py-scripts/ch07.py index 46f89979..c605ef9d 100644 --- a/code/optional-py-scripts/ch07.py +++ b/code/optional-py-scripts/ch07.py @@ -23,10 +23,8 @@ from sklearn.base import clone from sklearn.pipeline import _name_estimators from sklearn import datasets -from sklearn.cross_validation import train_test_split from sklearn.preprocessing import StandardScaler from sklearn.preprocessing import LabelEncoder -from sklearn.cross_validation import cross_val_score from sklearn.linear_model import LogisticRegression from sklearn.tree import DecisionTreeClassifier from sklearn.neighbors import KNeighborsClassifier @@ -34,11 +32,21 @@ from sklearn.metrics import roc_curve from sklearn.metrics import auc from sklearn.metrics import accuracy_score -from sklearn.grid_search import GridSearchCV from sklearn.ensemble import BaggingClassifier from sklearn.ensemble import AdaBoostClassifier from itertools import product +# Added version check for recent scikit-learn 0.18 checks +from distutils.version import LooseVersion as Version +from sklearn import __version__ as sklearn_version +if Version(sklearn_version) < '0.18': + from sklearn.cross_validation import train_test_split + from sklearn.cross_validation import cross_val_score + from sklearn.cross_validation import GridSearchCV +else: + from sklearn.model_selection import train_test_split + from sklearn.model_selection import cross_val_score + from sklearn.model_selection import GridSearchCV ############################################################################# print(50 * '=') @@ -48,7 +56,7 @@ def ensemble_error(n_classifier, error): k_start = math.ceil(n_classifier / 2.0) - probs = [comb(n_classifier, k) * error**k * (1-error)**(n_classifier - k) + probs = [comb(n_classifier, k) * error**k * (1 - error)**(n_classifier - k) for k in range(k_start, n_classifier + 1)] return sum(probs) @@ -185,11 +193,11 @@ def predict(self, X): for clf in self.classifiers_]).T maj_vote = np.apply_along_axis( - lambda x: - np.argmax(np.bincount(x, - weights=self.weights)), - axis=1, - arr=predictions) + lambda x: + np.argmax(np.bincount(x, + weights=self.weights)), + axis=1, + arr=predictions) maj_vote = self.lablenc_.inverse_transform(maj_vote) return maj_vote @@ -237,9 +245,9 @@ def get_params(self, deep=True): y = le.fit_transform(y) X_train, X_test, y_train, y_test =\ - train_test_split(X, y, - test_size=0.5, - random_state=1) + train_test_split(X, y, + test_size=0.5, + random_state=1) clf1 = LogisticRegression(penalty='l2', C=0.001, @@ -391,9 +399,19 @@ def get_params(self, deep=True): scoring='roc_auc') grid.fit(X_train, y_train) -for params, mean_score, scores in grid.grid_scores_: - print("%0.3f+/-%0.2f %r" - % (mean_score, scores.std() / 2.0, params)) +if Version(sklearn_version) < '0.18': + for params, mean_score, scores in grid.grid_scores_: + print("%0.3f +/- %0.2f %r" + % (mean_score, scores.std() / 2.0, params)) + +else: + cv_keys = ('mean_test_score', 'std_test_score', 'params') + + for r, _ in enumerate(grid.cv_results_['mean_test_score']): + print("%0.3f +/- %0.2f %r" + % (grid.cv_results_[cv_keys[0]][r], + grid.cv_results_[cv_keys[1]][r] / 2.0, + grid.cv_results_[cv_keys[2]][r])) print('Best parameters: %s' % grid.best_params_) print('Accuracy: %.2f' % grid.best_score_) @@ -426,9 +444,9 @@ def get_params(self, deep=True): y = le.fit_transform(y) X_train, X_test, y_train, y_test =\ - train_test_split(X, y, - test_size=0.40, - random_state=1) + train_test_split(X, y, + test_size=0.40, + random_state=1) tree = DecisionTreeClassifier(criterion='entropy', max_depth=None, diff --git a/code/optional-py-scripts/ch08.py b/code/optional-py-scripts/ch08.py index ab792868..c50145c5 100644 --- a/code/optional-py-scripts/ch08.py +++ b/code/optional-py-scripts/ch08.py @@ -17,7 +17,6 @@ import nltk from sklearn.feature_extraction.text import CountVectorizer from sklearn.feature_extraction.text import TfidfTransformer -from sklearn.grid_search import GridSearchCV from sklearn.pipeline import Pipeline from sklearn.linear_model import LogisticRegression from sklearn.feature_extraction.text import TfidfVectorizer @@ -26,6 +25,13 @@ from nltk.stem.porter import PorterStemmer from nltk.corpus import stopwords +# Added version check for recent scikit-learn 0.18 checks +from distutils.version import LooseVersion as Version +from sklearn import __version__ as sklearn_version +if Version(sklearn_version) < '0.18': + from sklearn.cross_validation import GridSearchCV +else: + from sklearn.model_selection import GridSearchCV ############################################################################# print(50 * '=') @@ -121,6 +127,7 @@ def preprocessor(text): ' '.join(emoticons).replace('-', '') return text + print('Preprocessor on Excerpt:\n\n', preprocessor(df.loc[0, 'review'][-50:])) res = preprocessor("This :) is :( a test :-)!") @@ -240,6 +247,7 @@ def stream_docs(path): text, label = line[:-3], int(line[-2]) yield text, label + next(stream_docs(path='./movie_data.csv')) diff --git a/code/optional-py-scripts/ch10.py b/code/optional-py-scripts/ch10.py index 25efda83..17e8eb98 100644 --- a/code/optional-py-scripts/ch10.py +++ b/code/optional-py-scripts/ch10.py @@ -25,6 +25,14 @@ from sklearn.tree import DecisionTreeRegressor from sklearn.ensemble import RandomForestRegressor +# Added version check for recent scikit-learn 0.18 checks +from distutils.version import LooseVersion as Version +from sklearn import __version__ as sklearn_version +if Version(sklearn_version) < '0.18': + from sklearn.cross_validation import train_test_split +else: + from sklearn.model_selection import train_test_split + ############################################################################# print(50 * '=') print('Section: Exploring the Housing dataset') @@ -112,7 +120,7 @@ def predict(self, X): sc_x = StandardScaler() sc_y = StandardScaler() X_std = sc_x.fit_transform(X) -y_std = sc_y.fit_transform(y) +y_std = sc_y.fit_transform(y[:, np.newaxis]).flatten() lr = LinearRegressionGD() lr.fit(X_std, y_std) @@ -131,6 +139,7 @@ def lin_regplot(X, y, model): plt.plot(X, model.predict(X), color='red', linewidth=2) return + lin_regplot(X_std, y_std, lr) plt.xlabel('Average number of rooms [RM] (standardized)') plt.ylabel('Price in $1000\'s [MEDV] (standardized)') @@ -143,7 +152,7 @@ def lin_regplot(X, y, model): print('Intercept: %.3f' % lr.w_[0]) -num_rooms_std = sc_x.transform([5.0]) +num_rooms_std = sc_x.transform(np.array([[5.0]])) price_std = lr.predict(num_rooms_std) print("Price in $1000's: %.3f" % sc_y.inverse_transform(price_std)) @@ -184,12 +193,21 @@ def lin_regplot(X, y, model): print(50 * '-') -ransac = RANSACRegressor(LinearRegression(), - max_trials=100, - min_samples=50, - residual_metric=lambda x: np.sum(np.abs(x), axis=1), - residual_threshold=5.0, - random_state=0) +if Version(sklearn_version) < '0.18': + ransac = RANSACRegressor(LinearRegression(), + max_trials=100, + min_samples=50, + residual_metric=lambda x: np.sum( + np.abs(x), axis=1), + residual_threshold=5.0, + random_state=0) +else: + ransac = RANSACRegressor(LinearRegression(), + max_trials=100, + min_samples=50, + loss='absolute_loss', + residual_threshold=5.0, + random_state=0) ransac.fit(X, y) inlier_mask = ransac.inlier_mask_ outlier_mask = np.logical_not(inlier_mask) diff --git a/code/optional-py-scripts/ch13.py b/code/optional-py-scripts/ch13.py index f41c683c..57941805 100644 --- a/code/optional-py-scripts/ch13.py +++ b/code/optional-py-scripts/ch13.py @@ -9,6 +9,7 @@ # License: MIT # https://github.com/rasbt/python-machine-learning-book/blob/master/LICENSE.txt +import os import theano from theano import tensor as T import numpy as np @@ -187,6 +188,7 @@ def predict_linreg(X, w): predict = theano.function(inputs=[Xt], givens={w: w}, outputs=net_input) return predict(X) + plt.scatter(X_train, y_train, marker='s', s=50) plt.plot(range(X_train.shape[0]), predict_linreg(X_train, w), @@ -228,6 +230,7 @@ def logistic_activation(X, w): z = net_input(X, w) return logistic(z) + print('P(y=1|x) = %.3f' % logistic_activation(X, w)[0]) @@ -273,6 +276,7 @@ def softmax_activation(X, w): z = net_input(X, w) return softmax(z) + y_probas = softmax(Z) print('Probabilities:\n', y_probas) @@ -293,6 +297,7 @@ def tanh(z): e_m = np.exp(-z) return (e_p - e_m) / (e_p + e_m) + z = np.arange(-5, 5, 0.005) log_act = logistic(z) tanh_act = tanh(z) @@ -358,6 +363,7 @@ def load_mnist(path, kind='train'): return images, labels + X_train, y_train = load_mnist('mnist', kind='train') print('Training rows: %d, columns: %d' % (X_train.shape[0], X_train.shape[1])) diff --git a/docs/2016-11-10-commoncause.png b/docs/2016-11-10-commoncause.png new file mode 100644 index 00000000..a18e3ad1 Binary files /dev/null and b/docs/2016-11-10-commoncause.png differ diff --git a/docs/equations/pymle-equations.pdf b/docs/equations/pymle-equations.pdf index 51b7cf30..90ed83f6 100644 Binary files a/docs/equations/pymle-equations.pdf and b/docs/equations/pymle-equations.pdf differ diff --git a/docs/equations/pymle-equations.tex b/docs/equations/pymle-equations.tex index 5c5cb15d..fec32ccf 100644 --- a/docs/equations/pymle-equations.tex +++ b/docs/equations/pymle-equations.tex @@ -13,7 +13,7 @@ \title{Python Machine Learning\\ Equation Reference} \author{Sebastian Raschka \\ \texttt{mail@sebastianraschka.com}} -\date{ \vspace{2cm} 05\slash 04\slash 2015 (last updated: 07\slash 06\slash 2016) \\\begin{flushleft} \vspace{2cm} \noindent\rule{10cm}{0.4pt} \\ Code Repository and Resources:: \href{https://github.com/rasbt/python-machine-learning-book}{https://github.com/rasbt/python-machine-learning-book} \vspace{2cm} \endgraf @book\{raschka2015python,\\ +\date{ \vspace{2cm} 05\slash 04\slash 2015 (last updated: 11\slash 29\slash 2016) \\\begin{flushleft} \vspace{2cm} \noindent\rule{10cm}{0.4pt} \\ Code Repository and Resources:: \href{https://github.com/rasbt/python-machine-learning-book}{https://github.com/rasbt/python-machine-learning-book} \vspace{2cm} \endgraf @book\{raschka2015python,\\ title=\{Python Machine Learning\},\\ author=\{Raschka, Sebastian\},\\ year=\{2015\},\\ @@ -432,7 +432,7 @@ \subsection{Logistic regression intuition and conditional probabilities} \phi(z) = P(y=1 | \mathbf{x}; \mathbf{w}) \] -given its features $x$ parameterized by the weights $w$. For example, if we compute $\phi(z) = 0.8$ for a particular flower sample, it means that the chance that this sample is an Iris-Versicolor ower is 80 percent. Similarly, the probability that this ower is an Iris-Setosa ower can be calculated as $P(y=0 | \mathbf{x};\mathbf{w})=1 - P (y=1 | \mathbf{x}; \mathbf{w}) = 0.2 or 20 percent.$ The predicted probability can then simply be converted into a binary outcome via a quantizer (unit step function): +given its features $\mathbf{x}$ parameterized by the weights $\mathbf{w}$. For example, if we compute $\phi(z) = 0.8$ for a particular flower sample, it means that the chance that this sample is an Iris-Versicolor flower is 80 percent. Similarly, the probability that this ower is an Iris-Setosa ower can be calculated as $P(y=0 | \mathbf{x};\mathbf{w})=1 - P (y=1 | \mathbf{x}; \mathbf{w}) = 0.2$ or 20 percent. The predicted probability can then simply be converted into a binary outcome via a quantizer (unit step function): \[ \hat{y}= \begin{cases} 1 & \text{ if } \phi(z) \ge 0.5 \\ @@ -972,7 +972,7 @@ \subsection{Computing the scatter matrices} \mathbf{S}_W = \sum^{c}_{i=1} \mathbf{S}_i \] -This is calculated by summing up the individual scatter matrices Si of each +This is calculated by summing up the individual scatter matrices $S_i$ of each individual class $i$: \[ @@ -1716,7 +1716,7 @@ \section{Turning a linear regression model into a curve - polynomial regression} In the previous sections, we assumed a linear relationship between explanatory and response variables. One way to account for the violation of linearity assumption is to use a polynomial regression model by adding polynomial terms: \[ -y = w_0 + w_1 x + w_2 x^2 x^2 + \dots + w_d x^d, +y = w_0 + w_1 x + w_2 x^2 + \dots + w_d x^d, \] where $d$ denotes the degree of the polynomial. diff --git a/docs/errata.md b/docs/errata.md index 1163d14e..ff4ce1bb 100644 --- a/docs/errata.md +++ b/docs/errata.md @@ -2,32 +2,28 @@ The *Known Errors* Leaderboard ======================== -### Note (2016-04-15) - ~~I am happy to say that layout team recently agreed to fix all the errors listed in the current errata! The fixes have already been applied, and I got a glance at the current version last -- it looks good :). So, based on what I've heard, the revised version will go online on April 19th, 2016 across the various platforms. If you got the book via Packt directly, you just need to log back in to re-download the .pdf, .epub, and/or .mobi files. Also, I was told that the same applies to the Kindle and iBooks versions and so forth. There may be a few delays depending on how fast the servers propagate the changes, but I will check back next week and post another update as soon as I see that the revision's gone life! Also, I want to say that I am really, really happy about all your feedback, and I really appreciate the nice words you are sending me about the book despite the little typos here and there! Thank you!~~ - -### Note (2016-04-23) - -**I just checked the e-book out via my Packt account; I am happy to announce that the revision has gone live! Based on my interpretation of the publisher's feedback, the revision should be available via the other platforms as well. Based on reader feedback, the revised version is also available via O'Reilly, and it's definitely available via Amazon (I've had the chance to look at a recent paperback). Please scroll down to the "Current Errata" section below for more information on the current state of the book.** - - ---- I tried my best to cut all the little typos, errors, and formatting bugs that slipped through the copy editing stage. Even so, I think it is just human to have a little typo here and there in a first edition. I know that this can be annoying as a reader, and I was thinking to associate it with something positive. Let's have a little leaderboard (inspired by Donald Knuth's "[Known Errors in My Books](http://www-cs-faculty.stanford.edu/~uno/books.html)"). **Every error that is not listed in the *Errata* yet will be rewarded with $1.** The only catch here is that you won't receive any single cent. Instead, I am going to donate the amount to [UNICEF USA](http://www.unicefusa.org), the US branch of the United Nations agency for raising funds to provide emergency food and healthcare for children in developing countries. + + + I would be happy if you just write me a short [mail](mailto:mail@sebastianraschka.com) including the error and page number, and please let me know if you want to be listed on the public leaderboard. ## Donations -- Current amount for the next donation: $17.00 +- Current amount for the next donation: $7.00 - Amount donated to charity: - [$39.00 2016-04-07](./2016-04-07-unicef.pdf) - [$76.00 2016-03-03](./2016-03-03-unicef.pdf) + - [$50.00 2016-11-10](./2016-11-10-commoncause.png) + ## Leaderboard @@ -50,6 +46,8 @@ I would be happy if you just write me a short [mail](mailto:mail@sebastianraschk 10. Panos N. ($2.00) 19. F. Liu ($2.00) 20. Stefan P. ($2.00) +32. Adam S. ($2.00) +33. Harry Hummel ($2.00) 11. Elias R. ($1.00) 12. Haitham H. Saleh ($1.00) 13. Muqueet M. ($1.00) @@ -65,6 +63,14 @@ I would be happy if you just write me a short [mail](mailto:mail@sebastianraschk 24. Justin H. ($1.00) 25. Neeraj K. ($1.00) 26. Attila B. ($1.00) +27. Simon C. ($1.00) +28. Andrew R. ($1.00) +29. Haesun P. ($1.00) +30. Raga M. ($1.00) +31. Ryszard T. Kaleta ($1.00) +32. Baiyu Z. ($1.00) + + ... @@ -93,6 +99,15 @@ This time, the easiest way may be to go to page 6 in chapter 1. Finally, the lab #### [Language Errata PDF v.3](http://sebastianraschka.com/pdf/books/pymle/errata_3rd_language.pdf) +
+
+
+
+
+
+
+
+ ### Old Errata: Oct 25, 2015 - Apr 22, 2016 diff --git a/docs/references.md b/docs/references.md index 3ddbd28e..92985d15 100644 --- a/docs/references.md +++ b/docs/references.md @@ -26,6 +26,8 @@ A BibTeX version for your favorite reference manager is available [here](./pymle ##### Additional Resources & Further Reading +- [Python Tutorial](https://www.scaler.com/topics/python) +

diff --git a/docs/running_jupyter_nb.pdf b/docs/running_jupyter_nb.pdf new file mode 100644 index 00000000..ff128a63 Binary files /dev/null and b/docs/running_jupyter_nb.pdf differ diff --git a/faq/README.md b/faq/README.md index cc84fff9..68fd5c5f 100644 --- a/faq/README.md +++ b/faq/README.md @@ -32,9 +32,9 @@ Sebastian - [What is the Definition of Data Science?](./definition_data-science.md) - [How do Data Scientists perform model selection? Is it different from Kaggle?](./model-selection-in-datascience.md) - ### Questions about the Machine Learning Field +- [How are Artificial Intelligence and Machine Learning related?](./ai-and-ml.md) - [What are some real-world examples of applications of machine learning in the field?](./ml-examples.md) - [What are the different fields of study in data mining?](./datamining-overview.md) - [What are differences in research nature between the two fields: machine learning & data mining?](./datamining-vs-ml.md) @@ -69,6 +69,7 @@ Sebastian ##### Model evaluation - [What is overfitting?](./overfitting.md) +- [How can I avoid overfitting?](./avoid-overfitting.md) - [Is it always better to have the largest possible number of folds when performing cross validation?](./number-of-kfolds.md) - [When training an SVM classifier, is it better to have a large or small number of support vectors?](./num-support-vectors.md) - [How do I evaluate a model?](./evaluate-a-model.md) @@ -133,6 +134,7 @@ Sebastian - [What is the difference between filter, wrapper, and embedded methods for feature selection?](./feature_sele_categories.md) - [Should data preparation/pre-processing step be considered one part of feature engineering? Why or why not?](./dataprep-vs-dataengin.md) - [Is a bag of words feature representation for text classification considered as a sparse matrix?](./bag-of-words-sparsity.md) +- [How can I apply an SVM to categorical data?](./svm_for_categorical_data.md) ##### Naive Bayes diff --git a/faq/ai-and-ml.md b/faq/ai-and-ml.md new file mode 100644 index 00000000..2676683c --- /dev/null +++ b/faq/ai-and-ml.md @@ -0,0 +1,13 @@ +# How are Artificial Intelligence and Machine Learning related? + +Artifical Intellicence (AI) started as a subfield of computer science with the focus on solving tasks that humans can but computers can't do (for instance, image recognition). AI can be approached in many ways, for example, writing a computer program that implements a set of rules devised by domain experts. Now, hand-crafting rules can be very laborious and time consuming. + +The field of machine learning -- originally, we can consider it as a subfield of AI -- was concerned with the development of algorithms so that computers can automatically learn (predictive) models from data. + +For instance, say we want to develop a program that can recognize handwritten digits from images. One would be to look at all of these images and come-up with a set of (nested) if-this-than-that rules to say which image is displayed in a particular image (for instance, by looking at the relative locations of pixels). Another approach would be to use a machine learning algorithm, which can fit a predictive model based on a thousands of labeled image samples that we may have collected in a database. Now, there's also deep learning, which in turn is a subfield of machine learning, referring to a particular subset of models that are particularly good at certain tasks such as image recognition and natural language processing. + +Or in short, machine learning (and deep learning) definitely helps to develop "AI," however, AI doesn't necessarily have to be developed using machine learning -- although, machine learning makes "AI" much more convenient ;). + +tldr; to summarize my point of view visually: + +![](ai-and-ml/ai-and-ml-1.png) diff --git a/faq/ai-and-ml/ai-and-ml-1.png b/faq/ai-and-ml/ai-and-ml-1.png new file mode 100644 index 00000000..1368369d Binary files /dev/null and b/faq/ai-and-ml/ai-and-ml-1.png differ diff --git a/faq/avoid-overfitting.md b/faq/avoid-overfitting.md new file mode 100644 index 00000000..30197d98 --- /dev/null +++ b/faq/avoid-overfitting.md @@ -0,0 +1,13 @@ +# How can I avoid overfitting? + +In short, the general strategies are to + +1. collect more data +2. use ensembling methods that "average" models +3. choose simpler models / penalize complexity + +For the first point, it may help to plot learning curves, plotting the training vs. the validation or cross-validation performance. If you see a trend that more data helps with closing the cap between the two, and if you could afford collecting more data, then this would probably the best choice. + +In my experience, ensembling is probably the most convenient way to build robust predictive models on somewhat small-sized datasets. As in real life, consulting a bunch of "experts" is usually not a bad idea before making a decision ;). + +Regarding the third point, I usually start a predictive modeling task with the simplest model as a benchmark: usually logistic regression. Overfitting can be a real problem if our model has too much capacity — too many model parameters to fit, and too many hyperparameters to tune. If the dataset is small, a simple model is always a good option to prevent overfitting, and it is also a good benchmark for comparison to more "complex" alternatives. diff --git a/faq/bagging-boosting-rf.md b/faq/bagging-boosting-rf.md index ba429455..4b74c14a 100644 --- a/faq/bagging-boosting-rf.md +++ b/faq/bagging-boosting-rf.md @@ -1,9 +1,9 @@ # How does the random forest model work? How is it different from bagging and boosting in ensemble models? -Let's assume we use a decision tree algorithms as base classifier for all three: boosting, bagging, and (obviously :)) the random forest. +Let's assume we use a decision tree algorithm as base classifier for all three: boosting, bagging, and (obviously :)) the random forest. -Why and when do we want to use any of these? Given a fixed-size number of training samples, our model will increasingly suffers from the "curse of dimensionality" if we increase the number of features. The challenge of individual, unpruned decision trees is that the hypothesis often ends up being too complex for the underlying training data -- decision trees are prone to overfitting. +Why and when do we want to use any of these? Given a fixed-size number of training samples, our model will increasingly suffer from the "curse of dimensionality" if we increase the number of features. The challenge of individual, unpruned decision trees is that the hypothesis often ends up being too complex for the underlying training data -- decision trees are prone to overfitting. **tl;dr: Bagging and random forests are "bagging" algorithms that aim to reduce the complexity of models that overfit the training data. In contrast, boosting is an approach to increase the complexity of models that suffer from high bias, that is, models that underfit the training data.** @@ -12,13 +12,13 @@ Why and when do we want to use any of these? Given a fixed-size number of traini ## Bagging -Now, let's take a look at the probably "simplest" case, bagging. Here, we train a number (ensemble) of decision trees from bootstrap samples of your training set. Bootstrap sampling means drawing random samples from our training set with replacement. E.g., if our training set consists of 7 training samples, our bootstrap samples (here: n=7) can look as follows, where C1, C2, ... Cm shall symbolize the decision tree classifiers: +Now, let's take a look at the probably "simplest" case, bagging. Here, we train a number (ensemble) of decision trees from bootstrap samples of our training set. Bootstrap sampling means drawing random samples from our training set with replacement. E.g., if our training set consists of 7 training samples, our bootstrap samples (here: n=7) can look as follows, where C1, C2, ... Cm shall symbolize the decision tree classifiers: ![](./bagging-boosting-rf/bagging.png) -After we trained your (m) decision trees, we can use them to classify new data via majority rule. For instance, we'd let each decision tree make a decision and predict the class label that received more votes. Typically, this would result in a less complex decision boundary, and the bagging classifier would have a lower variance (less overfitting) than an individual decision tree. Below is a plot comparing a single decision tree (left) to a bagging classifier (right) for 2 variables from the Wine dataset (Alcohol and Hue). +After we trained our (m) decision trees, we can use them to classify new data via majority rule. For instance, we'd let each decision tree make a decision and predict the class label that received more votes. Typically, this would result in a less complex decision boundary, and the bagging classifier would have a lower variance (less overfitting) than an individual decision tree. Below is a plot comparing a single decision tree (left) to a bagging classifier (right) for 2 variables from the Wine dataset (Alcohol and Hue). ![](./bagging-boosting-rf/bagging-regions.png) @@ -27,7 +27,7 @@ After we trained your (m) decision trees, we can use them to classify new data v ## Boosting -In contrast to bagging, you use very simple classifiers as base classifiers, so-called "weak learners." Picture these weak learners as "decision tree stumps" -- decision trees with only 1 splitting rule. Below, we will refer to the probably most popular example of boosting, AdaBoost. Here, we start with one decision tree stump (1) and "focus" on the samples it got wrong. In the next round, we train another decision tree stump that attempts to get these samples right (2); we achieve this by putting a larger weight on these training samples. Again, this 2nd classifier will likely get some other samples wrong, so you'd re-adjust the weights ... +In contrast to bagging, we use very simple classifiers as base classifiers, so-called "weak learners." Picture these weak learners as "decision tree stumps" -- decision trees with only 1 splitting rule. Below, we will refer to the probably most popular example of boosting, AdaBoost. Here, we start with one decision tree stump (1) and "focus" on the samples it got wrong. In the next round, we train another decision tree stump that attempts to get these samples right (2); we achieve this by putting a larger weight on these training samples. Again, this 2nd classifier will likely get some other samples wrong, so we'd re-adjust the weights ... ![](./bagging-boosting-rf/boosting.png) @@ -43,4 +43,4 @@ learning from mistakes. Eventually, we will come up with a model that has a lowe ## Random forests -The random forest algorithm is actually a bagging algorithm: also here, we draw random bootstrap samples from your training set. However, in addition to the bootstrap samples, we also draw random subsets of features for training the individual trees; in bagging, we provide each tree with the full set of features. Due to the random feature selection, the trees are more independent of each other compared to regular bagging, which often results in better predictive performance (due to better variance-bias trade-offs), and I'd say that it's also faster than bagging, because each tree learns only from a subset of features. +The random forest algorithm is actually a bagging algorithm: also here, we draw random bootstrap samples from our training set. However, in addition to the bootstrap samples, we also draw random subsets of features for training the individual trees; in bagging, we provide each tree with the full set of features. Due to the random feature selection, the trees are more independent of each other compared to regular bagging, which often results in better predictive performance (due to better variance-bias trade-offs), and I'd say that it's also faster than bagging, because each tree learns only from a subset of features. diff --git a/faq/choosing-technique.md b/faq/choosing-technique.md index f362cfca..db7e0bab 100644 --- a/faq/choosing-technique.md +++ b/faq/choosing-technique.md @@ -1,7 +1,4 @@ ---- -layout: faq -title: Machine Learning FAQ ---- + # What factors should I consider when choosing a predictive model technique? diff --git a/faq/clf-behavior-data.md b/faq/clf-behavior-data.md index 290fa899..03f93963 100644 --- a/faq/clf-behavior-data.md +++ b/faq/clf-behavior-data.md @@ -4,7 +4,7 @@ The visualization part is a bit tricky since we as humans are limited to 1-3 D g ![](./clf-behavior-data/iris.png) -(I've implemented this simple function here if you are interested: [mlxtend plot_decision_regions](http://rasbt.github.io/mlxtend/user_guide/evaluate/plot_decision_regions/).) +(I've implemented this simple function here if you are interested: [mlxtend plot_decision_regions](http://rasbt.github.io/mlxtend/user_guide/plotting/plot_decision_regions/).) Other than that, I think that synthetic datasets like "XOR," "half-moons," or concentric circles would be good candidates for evaluating classifier on non-linear problems:
diff --git a/faq/copyright.md b/faq/copyright.md index 5053f3c0..b8f239d8 100644 --- a/faq/copyright.md +++ b/faq/copyright.md @@ -2,8 +2,8 @@ Probably, you know me as a big advocate of *open source* and I like to share useful resources wherever and whenever I can! Most of my projects really benefit from resources people shared with me, the community, and the Internet as a whole. I am more than happy to do so likewise, that's one of the reasons why Python is so great, but this is a topic for another story ... :) -I am really passionate about machine learning, and other than using it for my own interests, I am truly excited about sharing knowledge, getting you excited about this field, and helping you on your path of becoming an affluent machine learning practitioner. It would make me really happy to hear if I was successful with my mission, and that you find the contents of my book are beneficial. If you are developing learning resources for other people, that's great, and if figures, code examples, math formulae, or passages are helpful for that, by all means, go for it! -Unfortunately though, writing a book for a/most publisher/s comes with some restrictions, but I have spoken with the content manager of this book, who in turn talked to the *Copyright Team*. +I am really passionate about machine learning, and other than using it for my own interests, I am truly excited about sharing knowledge, getting you excited about this field, and helping you on your path of becoming an affluent machine learning practitioner. It would make me really happy to hear if I was successful with my mission, and that you find the contents of my book are beneficial. If you are developing learning resources for other people, that's great, and if figures, code examples, math formulas, or passages are helpful for that, by all means, go for it! +Unfortunately though, writing a book for most publishers comes with some restrictions, but I have spoken with the content manager of this book, who in turn talked to the *Copyright Team*. > I hope you don’t mind if ask you a few quick questions about the copyright for the images since I couldn’t find anything specific about the rules on the Packt website. For example, if someone wants to use one of the images from the book in diff --git a/faq/cost-vs-loss.md b/faq/cost-vs-loss.md index c2abe443..e425ef56 100644 --- a/faq/cost-vs-loss.md +++ b/faq/cost-vs-loss.md @@ -1,8 +1,3 @@ ---- -layout: faq -title: Machine Learning FAQ ---- - # What is the difference between a cost function and a loss function in machine learning? The terms *cost* and *loss* functions are synonymous (some people also call it error function). The more general scenario is to define an objective function first, which we want to optimize. This objective function could be to diff --git a/faq/decisiontree-error-vs-entropy.md b/faq/decisiontree-error-vs-entropy.md index 2132826c..b9c8294e 100644 --- a/faq/decisiontree-error-vs-entropy.md +++ b/faq/decisiontree-error-vs-entropy.md @@ -60,7 +60,7 @@ Now, is it possible to learn this hypothesis (i.e., tree model) by minimizing th ![](./decisiontree-error-vs-entropy/Slide2.png) -As we can see, the Information Gain after the first split is exactly 0, since average classification error of the 2 child nodes is exactly the same as the classification error of the parent node (40/120 = 0.3333333). In this case, splitting the initial training set wouldn't yield any improvement in terms of our classification error criterion, and thus, the tree algorithm would stop at this point. +As we can see, the Information Gain after the first split is exactly 0, since average classification error of the 2 child nodes is exactly the same as the classification error of the parent node (40/120 = 0.3333333). In this case, splitting the initial training set wouldn't yield any improvement in terms of our classification error criterion, and thus, the tree algorithm would stop at this point (for this statement to be true, we have to make the assumption that neither splitting on feature x2 nor x3 would lead to an Information gain as well). Next, let's see what happens if we use Entropy as an impurity metric: diff --git a/faq/definition_data-science.md b/faq/definition_data-science.md index 176115d8..9fd962e8 100644 --- a/faq/definition_data-science.md +++ b/faq/definition_data-science.md @@ -1,8 +1,3 @@ ---- -layout: faq -title: Machine Learning FAQ ---- - # What is the Definition of Data Science? That's a tricky question. It's particularly challenging because there is no "definition." Unfortunately, this rather novel term has been used ambiguously, and there are many subjective definitions. Anyway, I think the field of Data Science is highly interdisciplinary and influenced by many many other fields ... diff --git a/faq/diff-perceptron-adaline-neuralnet.md b/faq/diff-perceptron-adaline-neuralnet.md index dde988a9..d2e3c148 100644 --- a/faq/diff-perceptron-adaline-neuralnet.md +++ b/faq/diff-perceptron-adaline-neuralnet.md @@ -71,10 +71,10 @@ Let me show you an example :) Here's the Python code if you want to reproduce these plots: ```Python -from mlxtend.evaluate import plot_decision_regions +from mlxtend.plotting import plot_decision_regions from mlxtend.classifier import Perceptron from mlxtend.classifier import Adaline -from mlxtend.classifier import NeuralNetMLP +from mlxtend.classifier import MultiLayerPerceptron import numpy as np import matplotlib.pyplot as plt from sklearn.datasets import make_moons @@ -90,19 +90,19 @@ ppn.fit(X, y) ada = Adaline(epochs=50, eta=0.05, random_seed=0) ada.fit(X, y) -mlp = NeuralNetMLP(n_output=len(np.unique(y)), - n_features=X.shape[1], - n_hidden=150, - l2=0.0, - l1=0.0, - epochs=500, - eta=0.01, - alpha=0.0, - decrease_const=0.0, - minibatches=1, - shuffle_init=False, - shuffle_epoch=False, - random_seed=0) +mlp = MultiLayerPerceptron(n_output=len(np.unique(y)), + n_features=X.shape[1], + n_hidden=150, + l2=0.0, + l1=0.0, + epochs=500, + eta=0.01, + alpha=0.0, + decrease_const=0.0, + minibatches=1, + shuffle_init=False, + shuffle_epoch=False, + random_seed=0) mlp = mlp.fit(X, y) diff --git a/faq/difference-deep-and-normal-learning.md b/faq/difference-deep-and-normal-learning.md index c0b3e942..517a321a 100644 --- a/faq/difference-deep-and-normal-learning.md +++ b/faq/difference-deep-and-normal-learning.md @@ -19,7 +19,7 @@ Now, if we add multiple hidden layers to this MLP, we'd also call the network "d **Deep Learning** -Now, this is where "deep learning" comes into play. Roughly speaking, we can think of deep learning as "clever" tricks or algorithms that can help us with the training of such "deep" neural network structures. There are many, many different neural network architectures, but to continue with the example of the MLP, let me introduce the idea of convolutional neural networks (ConvNets). We can think of those as an "add-on" to our MLP that helps we to detect features as "good" inputs for our MLP. +Now, this is where "deep learning" comes into play. Roughly speaking, we can think of deep learning as "clever" tricks or algorithms that can help us with the training of such "deep" neural network structures. There are many, many different neural network architectures, but to continue with the example of the MLP, let me introduce the idea of convolutional neural networks (ConvNets). We can think of those as an "add-on" to our MLP that helps us to detect features as "good" inputs for our MLP. In applications of "usual" machine learning, there is typically a strong focus on the feature engineering part; the model learned by an algorithm can only be so good as its input data. Of course, there must be sufficient discriminatory information in our dataset, however, the performance of machine learning algorithms can suffer substantially when the information is buried in meaningless features. The goal behind deep learning is to automatically learn the features from (somewhat) noisy data; it's about algorithms that do the feature engineering for us to provide deep neural network structures with meaningful information so that it can learn more effectively. **We can think of deep learning as algorithms for automatic "feature engineering," or we could simply call them "feature detectors," which help us to overcome the vanishing gradient challenge and facilitate the learning in neural networks with many layers.** diff --git a/faq/different.md b/faq/different.md index ba3db0a1..83ff1030 100644 --- a/faq/different.md +++ b/faq/different.md @@ -11,5 +11,5 @@ This is not yet just another "this is how scikit-learn works" book. I aim to exp
-Sure, this book will also contain a decent amount of "math & equations," and in my opinion, there is now way around it if we want to get away from the "black box thinking." However, I hope I managed to make it really easy to follow so that it can be read by a person who doesn't have a strong math background. Many parts of this book will provide examples in scikit-learn, in my opinion the most beautiful and practical machine learning library. However, we will also implement certain algorithms, which are not part of scikit-learn yet, by ourselves to boost our learning experience, for example, adaptive linear neurons, sequential feature selection algorithms, and multilayer artificial neural networks with backpropagation. +Sure, this book will also contain a decent amount of "math & equations," and in my opinion, there is no way around it if we want to get away from the "black box thinking." However, I hope I managed to make it really easy to follow so that it can be read by a person who doesn't have a strong math background. Many parts of this book will provide examples in scikit-learn, in my opinion the most beautiful and practical machine learning library. However, we will also implement certain algorithms, which are not part of scikit-learn yet, by ourselves to boost our learning experience, for example, adaptive linear neurons, sequential feature selection algorithms, and multilayer artificial neural networks with backpropagation. However, this book is not only about learning algorithms, but I also have a strong emphasis on "best practices" and everything that comes before and after the "model learning" in a machine learning application pipeline. Dealing with missing data, transforming categorical data into proper formats, extracting features, evaluating models via cross-validation, comparing algorithms with nested cross-validation, plotting receiver operator characteristics just to name a few ... All in all, this (350 page) short book provides you with everything you need to apply machine learning to real-world problem solving! diff --git a/faq/evaluate-a-model/evaluate_overview.eps b/faq/evaluate-a-model/evaluate_overview.eps new file mode 100644 index 00000000..35250e50 --- /dev/null +++ b/faq/evaluate-a-model/evaluate_overview.eps @@ -0,0 +1,8117 @@ +%!PS-Adobe-3.0 EPSF-3.0 +%%HiResBoundingBox: 0 0 720 540 +%%BoundingBox: 0 0 720 540 +%%Creator: Serif Affinity +%LanguageLevel: 3 +%%DocumentData: Clean7Bit +%ADO_ContainsXMP: MainFirst +%%EndComments +%%BeginProlog +101 dict begin +/m/moveto +/l/lineto +/c/curveto +3{load def}repeat +%%EndProlog +/currentdistillerparams where +{pop currentdistillerparams /CoreDistVersion get 5000 lt} {true} ifelse +{userdict /EPSHandler1_pdfmark /cleartomark load put +userdict /EPSHandler1_ReadMetadata_pdfmark {flushfile cleartomark} bind put} +{ userdict /EPSHandler1_pdfmark /pdfmark load put +userdict /EPSHandler1_ReadMetadata_pdfmark {/PUT 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a/faq/naive-bayes-vartypes.md +++ b/faq/naive-bayes-vartypes.md @@ -42,7 +42,7 @@ To come back to the original question, let us consider the multi-variate Bernoul We use the Bernoulli distribution to compute the likelihood of a binary variable. -For example, we could estimate P(xk=1 | ωj) via MLE as the frequency of occurences in the training set: +For example, we could estimate P(xk=1 | ωj) via MLE as the frequency of occurrences in the training set: θ = P̂(xk=1 | ωj) = Nxk, ωj / N ωj which reads "number of training samples in class ωj that have the property xk=1 (Nxk, ωj) divided by by all training samples in ωj (N ωj)." In context of text classification, this is basically the set of documents in class ωj that contain a particular word divided by all documents in ωj. Now, we can compute the likelihood of the binary feature vector **x** given class ωj as diff --git a/faq/scale-training-test.md b/faq/scale-training-test.md index 29b8f707..970b83e9 100644 --- a/faq/scale-training-test.md +++ b/faq/scale-training-test.md @@ -59,7 +59,7 @@ Now, let's say our model has learned the following hypotheses: It classifies sam - sample5: 6 cm -> class ? - sample6: 7 cm -> class ? -If we look at the "unstandardized “length in cm" values in our training datast, it is intuitive to say that all of these samples are likely belonging to class 2. However, if we standardize these by re-computing the *standard deviation* and and *mean* from the new data, we would get similar values as before (i.e., properties of a standard normal distribtion) in the training set and our classifier would (probably incorrectly) assign the “class 2” label to the samples 4 and 5. +If we look at the "unstandardized “length in cm" values in our training dataset, it is intuitive to say that all of these samples are likely belonging to class 2. However, if we standardize these by re-computing the *standard deviation* and and *mean* from the new data, we would get similar values as before (i.e., properties of a standard normal distribution) in the training set and our classifier would (probably incorrectly) assign the “class 2” label to the samples 4 and 5. - sample5: -1.21 -> class 2 - sample6: 0 -> class 2 diff --git a/faq/semi-vs-supervised.md b/faq/semi-vs-supervised.md index 65827c01..400b309a 100644 --- a/faq/semi-vs-supervised.md +++ b/faq/semi-vs-supervised.md @@ -2,7 +2,7 @@ Obviously, we are working with a labeled dataset when we are building (typically predictive) models using supervised learning. The goal of unsupervised learning is often of exploratory nature (clustering, compression) while working with unlabeled data. -In semi-supervised learning, we are basically trying to solve a supervised learning approach using labeled data, augmented by (typically a small amount of) unlabeled data. So, our goal is to overcome one of the problems of supervised learning -- having not enough labeled data. Adding cheap and abundant unlabeled data, we are hoping to build a better model than using supervised learning alone. +In semi-supervised learning, we are trying to solve a supervised learning approach using labeled data augmented by unlabeled data; the number of unlabeled or partially labeled samples is often larger than the number of labeled samples, since the former are less expensive and easier to obtain. So, our goal is to overcome one of the problems of supervised learning -- having not enough labeled data. Adding cheap and abundant unlabeled data, we are hoping to build a better model than using supervised learning alone. Although semi-supervised learning sounds like a powerful approach, we have to be careful. Semi-supervised learning is not always "the hammer to the nail" that we are looking for -- sometimes it works great, sometimes it doesn't. Here's a great paper on this: diff --git a/faq/svm_for_categorical_data.md b/faq/svm_for_categorical_data.md new file mode 100644 index 00000000..202a47e4 --- /dev/null +++ b/faq/svm_for_categorical_data.md @@ -0,0 +1,20 @@ +# How can I apply an SVM to categorical data? + +I assume you are asking about categorical features, not the target variable, which is already assumed to be categorical (binary) in SVM classifiers. + +First, there are two sub-types of categorical features: Ordinal and nominal features. + +Ordinal means that an "order" is implied. For example, a customer satisfaction metric {'satisfied', 'neutral', 'dissatisfied'} is a ordinal variable since we can order it: 'satisfied' > 'neutral' > 'dissatisfied'. Here, we can simply map the 'string' notation into an integer notation, for example 'satisfied'=1, 'neutral' =0, and 'dissatisfied'= -1. + +If our variable is *nominal*, an 'order' does not make sense. For example, think of 'color'; there are some cases in image processing where ordering color values makes sense, but for simplicity, we can't say 'red > blue > yellow' or so. To deal with such variables in SVM classification, we typically do a "one-hot" encoding. Here, we create so-called dummy variables that can binary values — we create one dummy variable for each possible value of that nominal feature variable. Say that our color variable can have one of the three values: 'red,' 'blue,' 'yellow.' And Let's say we have the following dataset consisting of 4 training samples: + +- sample 1: 'blue' +- sample 2: 'yellow' +- sample 3: 'red' +- sample 4: 'yellow' + +Then our one-hot encoding would look like this: + +![](svm_for_categorical_data/onehot-color.png) + +Note that there's only one "true" value (the integer 1) in each row, which denotes the column for that sample in the training set. Sample 1 is blue; sample 2 is yellow, and so forth. diff --git a/faq/svm_for_categorical_data/onehot-color.png b/faq/svm_for_categorical_data/onehot-color.png new file mode 100644 index 00000000..4759f23e Binary files /dev/null and b/faq/svm_for_categorical_data/onehot-color.png differ diff --git a/faq/tensorflow-vs-scikitlearn.md b/faq/tensorflow-vs-scikitlearn.md index 38e2a9dd..57cae08d 100644 --- a/faq/tensorflow-vs-scikitlearn.md +++ b/faq/tensorflow-vs-scikitlearn.md @@ -37,7 +37,7 @@ lr.fit(X, y) In addition, I have a little helper function to plot the 2D decision surface: ```python -from mlxtend.evaluate import plot_decision_regions +from mlxtend.plotting import plot_decision_regions plot_decision_regions(X, y, clf=lr) plt.title('Softmax Regression in scikit-learn') @@ -131,7 +131,7 @@ plt.show() ```python -from mlxtend.evaluate import plot_decision_regions +from mlxtend.plotting import plot_decision_regions plot_decision_regions(X, y, clf=lr) plt.title('Softmax Regression via Gradient Descent in TensorFlow') @@ -139,3 +139,7 @@ plt.show() ``` ![](./tensorflow-vs-scikitlearn/tf_softmax.png) + +**Note** + +I've removed the TensorFlow code from mlxtend because it became pretty inconvenient to maintain. The original code should still be available through GitHub. E.g., if you install mlxtend 0.5.1, (`pip install mlxtend=0.5.1`) or browse through the files here: https://github.com/rasbt/mlxtend/tree/86e40d5af5222d78acf219cc8188cfd28a972d9e/mlxtend/tf_classifier diff --git a/faq/underscore-convention.md b/faq/underscore-convention.md index 01307e04..35937b44 100644 --- a/faq/underscore-convention.md +++ b/faq/underscore-convention.md @@ -18,14 +18,15 @@ instead of def sigmoid(self, z): return 1.0 / (1.0 + np.exp(-z)) -The short answer is, the trailing underscore (`self.gamma_`) in class attributes is a scikit-learn convention to denote "estimated" or "fitted" attributes. The leading underscores are (`_sigmoid(self, z)`) denote private methods that the user shouldn't bother with. +The short answer is, the trailing underscore (`self.gamma_`) in class attributes is a scikit-learn convention to denote "estimated" or "fitted" attributes. +The leading underscores are (`_sigmoid(self, z)`) denote private methods that the user should not bother with. In brief: As a reader, you can safely ignore those underscores, however, if you are curious about their intention, please read on! ## Leading underscores in class methods -The usage of underscores for naming class methods is a common Python convention to distinguish between private and public methods. Basically, you don't want the user to worry about these private methods, which is why they don't appear in the help menu. +The usage of underscores for naming class methods is a common Python convention to distinguish between private and public methods. Basically, you do not want the user to worry about these private methods, which is why they do not appear in the help menu. class MyClass(object): def __init__(self, param='some_value'): @@ -67,7 +68,7 @@ The usage of underscores for naming class methods is a common Python convention * Note that `__init__` is an exception, `__init__` is a special method that is required to initialize a class. -Let’s initialize a new object and call this “public” class: +Let us initialize a new object and call this "public" class: >>> MyObj = MyClass() >>> MyObj.public() @@ -81,7 +82,7 @@ The single underscore in `_indicate_private` indicates privacy. Typically, priva - Please keep in mind that calling private methods is at your own risk; the developers usually take no responsibilities for odd things that may happen if you call private methods as a user. -The indication of “privacy” is a bit stronger if we use 2 preceding underscores, for example, calling the `__pseudo_private` method directly like a regular method doesn’t work anymore: +The indication of "privacy" is a bit stronger if we use 2 preceding underscores, for example, calling the `__pseudo_private` method directly like a regular method does not work anymore: >>> MyObj.__pseudo_private() --------------------------------------------------------------------------- @@ -91,7 +92,7 @@ The indication of “privacy” is a bit stronger if we use 2 preceding undersco AttributeError: 'MyClass' object has no attribute '__pseudo_private' -To call the a private methods that is prefaced with 2 underscores, we need to adhere to the “name mangling” rules; that is, we need to add a `_classname` prefix, to call the method, for example, +To call the a private methods that is prefaced with 2 underscores, we need to adhere to the "name mangling" rules; that is, we need to add a `_classname` prefix, to call the method, for example, >>> MyObj._MyClass__pseudo_private() 'really private method' @@ -100,16 +101,16 @@ To call the a private methods that is prefaced with 2 underscores, we need to ad ## Class attributes with trailing underscores -In contrast to the leading underscore, the trailing underscores in class attributes don't any "technical" effects. In fact, this is just a convention that I adopted from scikit-learn out of habit. +In contrast to the leading underscore, the trailing underscores in class attributes do not have any "technical" effects. In fact, this is just a convention that I adopted from scikit-learn out of habit. Here are two excerpts from the scikit-learn [developer/contributor documentation](http://scikit-learn.org/stable/developers/): -> Attributes that have been estimated from the data must always have a name ending with trailing underscore, for example, the coefficients of some regression estimator would be stored in a coef_ attribute after fit has been called. +> Attributes that have been estimated from the data must always have a name ending with trailing underscore `_`, for example, the coefficients of some regression estimator would be stored in a `coef_` attribute after `fit()` has been called. -> Also it is expected that parameters with trailing _ are not to be set inside the ``__init__`` method. All and only the public attributes set by fit have a trailing _. As a result the existence of parameters with trailing _ is used to check if the estimator has been fitted. +> Also it is expected that parameters with trailing underscore `_` are not to be set inside the ``__init__`` method. All and only the public attributes set by `fit()` have a trailing `_`. As a result the existence of parameters with trailing `_` is used to check if the estimator has been fitted. -To see it in action, let's create a primitive `Estimator`: +To see it in action, let us create a primitive `Estimator`: class MyEstimator(): def __init__(self): @@ -118,7 +119,7 @@ To see it in action, let's create a primitive `Estimator`: def fit(self): self.fit_param_ = 0.1 -Intuitively, attributes that are in `__init__` are accessible after we initialized a new object +Intuitively, attributes that are in `__init__` are accessible after we initialized a new object: >>> est = MyEstimator() >>> est.param diff --git a/images/CRBadgeNotableBook.jpg b/images/CRBadgeNotableBook.jpg new file mode 100644 index 00000000..bd4adfaa Binary files /dev/null and b/images/CRBadgeNotableBook.jpg differ diff --git a/images/check_env.png b/images/check_env.png new file mode 100644 index 00000000..2846d607 Binary files /dev/null and b/images/check_env.png differ diff --git a/images/equation-ref-logo.png b/images/equation-ref-logo.png new file mode 100644 index 00000000..32878dd9 Binary files /dev/null and b/images/equation-ref-logo.png differ diff --git a/images/pymle-cover_cn.jpg b/images/pymle-cover_cn.jpg new file mode 100644 index 00000000..058e7919 Binary files /dev/null and b/images/pymle-cover_cn.jpg differ diff --git a/images/pymle-cover_cn_mainland.jpg b/images/pymle-cover_cn_mainland.jpg new file mode 100644 index 00000000..1cc51ea1 Binary files /dev/null and b/images/pymle-cover_cn_mainland.jpg differ diff --git a/images/pymle-cover_de.jpg b/images/pymle-cover_de.jpg index 209bf600..8bc3ba54 100644 Binary files a/images/pymle-cover_de.jpg and b/images/pymle-cover_de.jpg differ diff --git a/images/pymle-cover_de_old.jpg b/images/pymle-cover_de_old.jpg new file mode 100644 index 00000000..209bf600 Binary files /dev/null and b/images/pymle-cover_de_old.jpg differ diff --git a/images/pymle-cover_it.jpg b/images/pymle-cover_it.jpg new file mode 100644 index 00000000..4370df7d Binary files /dev/null and b/images/pymle-cover_it.jpg differ diff --git a/images/pymle-cover_jp.jpg b/images/pymle-cover_jp.jpg index 36609142..0884ce47 100644 Binary files a/images/pymle-cover_jp.jpg and b/images/pymle-cover_jp.jpg differ diff --git a/images/pymle-cover_kr.jpg b/images/pymle-cover_kr.jpg new file mode 100644 index 00000000..571a5177 Binary files /dev/null and b/images/pymle-cover_kr.jpg differ diff --git a/images/pymle-cover_pl.jpg b/images/pymle-cover_pl.jpg new file mode 100644 index 00000000..859f5436 Binary files /dev/null and b/images/pymle-cover_pl.jpg differ diff --git a/images/pymle-cover_ru.jpg b/images/pymle-cover_ru.jpg new file mode 100644 index 00000000..7c29d3bd Binary files /dev/null and b/images/pymle-cover_ru.jpg differ diff --git a/images/pymle_cover_double_small.jpg b/images/pymle_cover_double_small.jpg new file mode 100644 index 00000000..2a9303b3 Binary files /dev/null and b/images/pymle_cover_double_small.jpg differ