Random Forest Image Classifier Trainer in weka - Java Machine Learning AI

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Description

Random Forest Image Classifier Trainer in weka

Demo Code

import java.io.File;

import weka.classifiers.functions.LibSVM;
import weka.classifiers.trees.RandomForest;
import weka.core.Attribute;
import weka.core.Instances;
import weka.core.SerializationHelper;
import weka.core.converters.ArffLoader;
import weka.core.converters.Loader;
import weka.gui.beans.Classifier;

public class RandomForestImageClassifierTrainer {

    public static void main(String args[]) throws Exception {
        ArffLoader trainLoader = new ArffLoader();
        trainLoader.setSource(new File("train.arff"));
        trainLoader.setRetrieval(Loader.BATCH);
        Instances trainDataSet = trainLoader.getDataSet();
        Attribute trainAttribute = trainDataSet.attribute("class");

        trainDataSet.setClass(trainAttribute);
        //trainDataSet.deleteStringAttributes();

        RandomForest classifier = new RandomForest();
        classifier.setNumTrees(500);/*w  ww .  j a  v  a 2 s. c om*/
        classifier.setMaxDepth(30);
        classifier.setDebug(true);

        final double startTime = System.currentTimeMillis();
        classifier.buildClassifier(trainDataSet);
        final double endTime = System.currentTimeMillis();
        double executionTime = (endTime - startTime) / (1000.0);
        System.out.println("Total execution time: " + executionTime);

        SerializationHelper.write("classifier500.model", classifier);
        System.out.println("Saved trained model to classifier.model");
    }
}

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