Example usage for weka.classifiers.trees DecisionStump buildClassifier

Introduction

In this page you can find the example usage for weka.classifiers.trees DecisionStump buildClassifier.

Prototype

public void buildClassifier(Instances instances) throws Exception 

Source Link

Document

Generates the classifier.

Usage

From source file:fantail.algorithms.RankingByPairwiseComparison.java

License:Open Source License

@Override
public void buildRanker(Instances data) throws Exception {
    m_Classifiers = new ArrayList<weka.classifiers.AbstractClassifier>();
    m_AlgoPairs = new ArrayList<String>();
    m_NumLabels = Tools.getNumberTargets(data);

    // build pb datasets
    for (int a = 0; a < m_NumLabels; a++) {
        for (int b = 0; b < m_NumLabels; b++) {

            String pairStr = a + "|" + b;
            if (!hasPair(m_AlgoPairs, pairStr) && a != b) {
                m_AlgoPairs.add(pairStr);

                Instances d = new Instances(data);
                d.setClassIndex(-1);/*w  w w.j a  v  a2s  . co m*/
                d.deleteAttributeAt(d.numAttributes() - 1);

                weka.filters.unsupervised.attribute.Add add = new weka.filters.unsupervised.attribute.Add();
                add.setInputFormat(d);
                add.setOptions(weka.core.Utils
                        .splitOptions("-T NOM -N class -L " + ((int) a) + "," + ((int) b) + " -C last"));

                d = Filter.useFilter(d, add);
                d.setClassIndex(d.numAttributes() - 1);

                for (int i = 0; i < d.numInstances(); i++) {

                    Instance metaInst = (Instance) data.instance(i);
                    Instance inst = d.instance(i);

                    double[] rankVector = Tools.getTargetVector(metaInst);

                    double rank_a = rankVector[a];
                    double rank_b = rankVector[b];

                    if (rank_a < rank_b) {
                        inst.setClassValue(0.0);
                    } else {
                        inst.setClassValue(1.0);
                    }
                }

                //weka.classifiers.functions.SMO cls = new weka.classifiers.functions.SMO();
                //String ops = "weka.classifiers.functions.SMO -C 1.0 -L 0.001 -P 1.0E-12 -N 0 -V -1 -W 1 -K \"weka.classifiers.functions.supportVector.RBFKernel -C 250007 -G 0.01\"";
                //cls.setOptions(weka.core.Utils.splitOptions(ops));                   
                //cls.buildClassifier(d);
                //weka.classifiers.functions.Logistic cls = new weka.classifiers.functions.Logistic();
                //weka.classifiers.trees.J48 cls = new weka.classifiers.trees.J48();
                //weka.classifiers.rules.ZeroR cls = new weka.classifiers.rules.ZeroR();
                weka.classifiers.trees.DecisionStump cls = new weka.classifiers.trees.DecisionStump();
                cls.buildClassifier(d);
                m_Classifiers.add(cls);
                m_BaseClassifierName = cls.getClass().getSimpleName();
                m_Add = add;
            }
        }
    }
}

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