training the weka naive bayes classifier - Java Machine Learning AI

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Description

training the weka naive bayes classifier

Demo Code

import java.io.File;

import weka.classifiers.bayes.NaiveBayes;
import weka.core.Instances;
import weka.core.converters.ArffSaver;
import weka.core.converters.ConverterUtils.DataSource;
import weka.filters.Filter;
import weka.filters.supervised.attribute.AddClassification;

public class OutputPredictToTestFile {
    public static void main(String[] args) throws Exception {

        DataSource source = new DataSource("iris-train.arff");
        Instances traindata = source.getDataSet();
        traindata.setClassIndex(traindata.numAttributes() - 1);
        DataSource source2 = new DataSource("iris-unknown.arff");
        Instances testdata = source2.getDataSet();
        testdata.setClassIndex(testdata.numAttributes() - 1);
        /**/*from w  w w .  j  ava 2 s  .co  m*/
         * training the naive bayes classifier
         */
        NaiveBayes nb = new NaiveBayes();
        /**
         * filter the data and output the prediction to test file
         */
        AddClassification addClass = new AddClassification();
        addClass.setClassifier(nb);
        addClass.setRemoveOldClass(true);
        addClass.setOutputClassification(true);
        addClass.setInputFormat(traindata);
        Filter.useFilter(traindata, addClass);
        Instances newtestdata = Filter.useFilter(testdata, addClass);
        ArffSaver saver = new ArffSaver();
        saver.setInstances(newtestdata);
        saver.setFile(new File("iris-new.arff"));
        saver.writeBatch();

    }

}

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