Example usage for weka.filters.unsupervised.instance Resample setNoReplacement

Introduction

In this page you can find the example usage for weka.filters.unsupervised.instance Resample setNoReplacement.

Prototype

public void setNoReplacement(boolean value) 

Source Link

Document

Sets whether instances are drawn with or with out replacement.

Usage

From source file:fantail.algorithms.ARTForests.java

License:Open Source License

@Override
public void buildRanker(Instances metaData) throws Exception {

    Random r = new Random(m_RandomSeed);
    Instances workingData = new Instances(metaData);
    m_WeakRankers = new Ranker[m_T];

    for (int i = 0; i < m_T; i++) {
        Instances baggingSample = workingData.resampleWithWeights(r);

        if (m_BaggingPercentage < 100.0) {
            weka.filters.unsupervised.instance.Resample res = new weka.filters.unsupervised.instance.Resample();
            res.setSampleSizePercent(m_BaggingPercentage);
            res.setNoReplacement(false);
            res.setInputFormat(baggingSample);
            baggingSample = Filter.useFilter(baggingSample, res);
        }//from   w ww . java  2s .  c o m

        BinaryART ranker = new BinaryART();
        ranker.setMiniLeaf(m_NumMinInstances);
        ranker.setK(m_K);
        ranker.setRandomSeed(i);
        ranker.setUseMedian(m_UseMedian);

        m_WeakRankers[i] = ranker;
        m_WeakRankers[i].buildRanker(baggingSample);
    }
}

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From source file:hero.unstable.util.classification.wekaData.java

public void setData(String dataPath, double percentageClaseControl, int classIdx) {
    // Load data//from www  . j a va2s. c om
    //Instances data = IO.csvToInstances(dataPath);
    ConverterUtils.DataSource source = null;
    try {
        source = new ConverterUtils.DataSource(dataPath);
        dataOriginal = source.getDataSet();
    } catch (Exception ex) {
        logger.info(ClusteringBinaryPD.class.getName());
        ex.printStackTrace();
    }

    // Set first column as CLASS
    dataOriginal.setClassIndex(classIdx);
    //logger.info("Data correctly loaded from " + dataPath);
    //logger.info("Data filtered: Class is the FIRST column");
    //logger.info("Number of attributes: " + data.numAttributes() );
    //logger.info("Number of instances: " + data.numInstances() );
    // Get TRAINING and TEST sets:
    Resample splitter = new Resample();
    try {
        splitter.setInvertSelection(false);
        splitter.setNoReplacement(true);
        splitter.setSampleSizePercent(percentageClaseControl);
        splitter.setInputFormat(dataOriginal);
        dataTraining = Filter.useFilter(dataOriginal, splitter);

        splitter = new Resample();
        splitter.setInvertSelection(true);
        splitter.setNoReplacement(true);
        splitter.setSampleSizePercent(percentageClaseControl);
        splitter.setInputFormat(dataOriginal);
        dataTest = Filter.useFilter(dataOriginal, splitter);
    } catch (Exception ex) {
        Logger.getLogger(ClusteringBinaryPD.class.getName()).log(Level.SEVERE, null, ex);
    }
}

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