Example usage for weka.filters.unsupervised.attribute Add setOptions

Introduction

In this page you can find the example usage for weka.filters.unsupervised.attribute Add setOptions.

Prototype

@Override
public void setOptions(String[] options) throws Exception 

Source Link

Document

Parses a given list of options.

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);//from   w  w  w.  j av a  2 s.c  o 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;
            }
        }
    }
}

---