RandomForest.java

import java.io.File;

import weka.classifiers.Classifier;
import weka.classifiers.Evaluation;
import weka.core.Instances;
import weka.core.converters.ArffLoader;
import weka.filters.Filter;
import weka.filters.unsupervised.attribute.StringToWordVector;
import java.io.IOException;
import weka.classifiers.trees.RandomForest;

public class RandomForest {

	/** file names are defined*/
	public static final String TRAINING_DATA_SET_FILENAME="decision-train.arff";
	public static final String TESTING_DATA_SET_FILENAME="decision-test.arff";
	

	/**
	 * This method is to load the data set.
	 * @param fileName
	 * @return
	 * @throws IOException
	 */
	public static Instances getDataSet(String fileName) throws IOException {
		/**
		 * we can set the file i.e., loader.setFile("finename") to load the data
		 */
		int classIdx = 1;
		/** the arffloader to load the arff file */
		ArffLoader loader = new ArffLoader();
		/** load the traing data */
		loader.setSource(RandomForestDemo.class.getResourceAsStream("/" + fileName));
		/**
		 * we can also set the file like loader3.setFile(new
		 * File("test-confused.arff"));
		 */
		//loader.setFile(new File(fileName));
		Instances dataSet = loader.getDataSet();
		/** set the index based on the data given in the arff files */
		dataSet.setClassIndex(classIdx);
		return dataSet;
	}

	public static void process() throws Exception {

		Instances trainingDataSet = getDataSet(TRAINING_DATA_SET_FILENAME);
		Instances testingDataSet = getDataSet(TESTING_DATA_SET_FILENAME);
		
		RandomForest forest=new RandomForest();
		forest.setNumTrees(10);
		
		forest.buildClassifier(trainingDataSet);
		Evaluation eval = new Evaluation(trainingDataSet);
		eval.evaluateModel(forest, testingDataSet);
		
		
		/** Print the algorithm summary */
		System.out.println("** Decision Tress Evaluation with Datasets **");
		System.out.println(eval.toSummaryString());
		System.out.print(" the expression for the input data as per alogorithm is ");
		System.out.println(forest);
		System.out.println(eval.toMatrixString());
		System.out.println(eval.toClassDetailsString());
		
	}
}