Example usage for weka.classifiers CostMatrix setElement

Introduction

In this page you can find the example usage for weka.classifiers CostMatrix setElement.

Prototype

public final void setElement(int rowIndex, int columnIndex, double value) 

Source Link

Document

Set the value of a cell as a double

Usage

From source file:etc.aloe.cscw2013.TrainingImpl.java

License:Open Source License

@Override
public WekaModel train(ExampleSet examples) {
    System.out.println("SMO Options: " + SMO_OPTIONS);
    SMO smo = new SMO();
    try {/*  w  w w  .j  a  v  a  2s  . c o  m*/
        smo.setOptions(Utils.splitOptions(SMO_OPTIONS));
    } catch (Exception ex) {
        System.err.println("Unable to configure SMO.");
        System.err.println("\t" + ex.getMessage());
        return null;
    }

    //Build logistic models if desired
    smo.setBuildLogisticModels(isBuildLogisticModel());

    Classifier classifier = smo;

    if (useCostTraining) {
        CostSensitiveClassifier cost = new CostSensitiveClassifier();
        cost.setClassifier(smo);
        CostMatrix matrix = new CostMatrix(2);
        matrix.setElement(0, 0, 0);
        matrix.setElement(0, 1, falsePositiveCost);
        matrix.setElement(1, 0, falseNegativeCost);
        matrix.setElement(1, 1, 0);
        cost.setCostMatrix(matrix);

        classifier = cost;

        System.out.print("Wrapping SMO in CostSensitiveClassifier " + matrix.toMatlab());

        if (useReweighting) {
            cost.setMinimizeExpectedCost(false);
            System.out.println(" using re-weighting.");
        } else {
            cost.setMinimizeExpectedCost(true);
            System.out.println(" using min-cost criterion.");
        }
    }

    try {
        System.out.print("Training SMO on " + examples.size() + " examples... ");
        classifier.buildClassifier(examples.getInstances());
        System.out.println("done.");

        WekaModel model = new WekaModel(classifier);
        return model;
    } catch (Exception ex) {
        System.err.println("Unable to train SMO.");
        System.err.println("\t" + ex.getMessage());
        return null;
    }
}

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From source file:org.openml.webapplication.algorithm.InstancesHelper.java

License:Open Source License

public static CostMatrix doubleToCostMatrix(double[][] cm) {
    CostMatrix costmatrix = new CostMatrix(cm.length);
    for (int i = 0; i < cm.length; ++i) {
        for (int j = 0; j < cm[i].length; ++j) {
            costmatrix.setElement(i, j, cm[i][j]);
        }//from   w w  w . j  a  v a 2 s  .c  om
    }
    return costmatrix;
}

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