Example usage for weka.attributeSelection AttributeSelection setRanking

Introduction

In this page you can find the example usage for weka.attributeSelection AttributeSelection setRanking.

Prototype

public void setRanking(boolean r) 

Source Link

Document

produce a ranking (if possible with the set search and evaluator)

Usage

From source file:mlflex.WekaInMemoryLearner.java

License:Open Source License

@Override
protected ArrayList<String> SelectOrRankFeatures(ArrayList<String> algorithmParameters,
        DataInstanceCollection trainData, DataInstanceCollection dependentVariableInstances) throws Exception {
    ArrayList<String> dataPointNames = Lists.SortStringList(trainData.GetDataPointNames());

    FastVector attVector = GetAttributeVector(dependentVariableInstances, dataPointNames, trainData);
    Instances instances = GetInstances(dependentVariableInstances, attVector, trainData);

    AttributeSelection attsel = new AttributeSelection();
    ASEvaluation eval = GetAttributeEvaluator(algorithmParameters);
    ASSearch search = GetSearchMethod(algorithmParameters);
    attsel.setEvaluator(eval);// www .j  a  va 2 s . c  om
    attsel.setSearch(search);

    boolean isRanker = algorithmParameters.get(2).equals(Ranker.class.getName());

    if (isRanker)
        attsel.setRanking(true);

    attsel.SelectAttributes(instances);

    ArrayList<String> features = new ArrayList<String>();

    if (isRanker) {
        for (double[] rank : attsel.rankedAttributes())
            features.add(instances.attribute((int) rank[0]).name());
    } else {
        for (int i : attsel.selectedAttributes())
            features.add(instances.attribute(i).name());
    }

    instances = null;

    return features;
}

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