Using classifiers Vote filter - Java Machine Learning AI

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Description

Using classifiers Vote filter

Demo Code

import weka.attributeSelection.BestFirst;
import weka.attributeSelection.CfsSubsetEval;
import weka.classifiers.Evaluation;
import weka.classifiers.meta.CVParameterSelection;
import weka.classifiers.meta.Vote;
import weka.core.Instances;
import weka.core.Utils;
import weka.filters.Filter;
import weka.filters.supervised.attribute.AttributeSelection;
import java.io.BufferedReader;
import java.io.FileReader;
import java.io.FileWriter;
import java.io.PrintWriter;

public class VotingWithFilter {
    public static void main(String[] args) throws Exception {
        Instances train = new Instances(new BufferedReader(new FileReader(
                "spambase_train.arff")));
        Instances test = new Instances(new BufferedReader(new FileReader(
                "spambase_test.arff")));
        train.setClassIndex(train.numAttributes() - 1);
        test.setClassIndex(test.numAttributes() - 1);
        //set up filter of the data
        AttributeSelection filter = new AttributeSelection();
        BestFirst search = new BestFirst();
        search.setOptions(weka.core.Utils.splitOptions("-D 2 -N 10"));
        filter.setEvaluator(new CfsSubsetEval());
        filter.setSearch(search);//from   w  w  w . j av  a2  s .  c  o  m
        filter.setInputFormat(train);
        Instances newtrain = Filter.useFilter(train, filter);
        Instances newtest = Filter.useFilter(test, filter);
        newtrain.setClassIndex(newtrain.numAttributes() - 1);
        newtest.setClassIndex(newtest.numAttributes() - 1);

        Vote vs = new Vote();
        vs.setOptions(weka.core.Utils
                .splitOptions("-B \"weka.classifiers.functions.SMO\" -B \"weka.classifiers.trees.LMT\" -B \"weka.classifiers.trees.RandomForest -I 10 -K 0\" -R AVG"));

        System.out.println(Utils.joinOptions(vs.getOptions()));

        vs.buildClassifier(newtrain);
        PrintWriter pw = new PrintWriter(new FileWriter(
                "spambase-L5.txt"));

        for (int i = 0; i < newtest.numInstances(); i++) {
            double pred = vs.classifyInstance(newtest.instance(i));
            pw.println(pred);
        }
        pw.close();
    }
}

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