Example usage for weka.classifiers.evaluation EvaluationUtils getTestPredictions

Introduction

In this page you can find the example usage for weka.classifiers.evaluation EvaluationUtils getTestPredictions.

Prototype

public ArrayList<Prediction> getTestPredictions(Classifier classifier, Instances test) throws Exception 

Source Link

Document

Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.

Usage

From source file:trainableSegmentation.Weka_Segmentation.java

License:GNU General Public License

/**
 * Display the threshold curve window (for precision/recall, ROC, etc.).
 *
 * @param data input instances/* www  .j  av a2 s . c o  m*/
 * @param classifier classifier to evaluate
 */
public static void displayGraphs(Instances data, AbstractClassifier classifier) {
    ThresholdCurve tc = new ThresholdCurve();

    FastVector predictions = null;
    try {
        final EvaluationUtils eu = new EvaluationUtils();
        predictions = eu.getTestPredictions(classifier, data);
    } catch (Exception e) {
        IJ.log("Error while evaluating data!");
        e.printStackTrace();
        return;
    }

    Instances result = tc.getCurve(predictions);
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setName(result.relationName() + " (display only)");
    PlotData2D tempd = new PlotData2D(result);
    tempd.setPlotName(result.relationName());
    tempd.addInstanceNumberAttribute();
    try {
        vmc.addPlot(tempd);
    } catch (Exception e) {
        IJ.log("Error while adding plot to visualization panel!");
        e.printStackTrace();
        return;
    }
    String plotName = vmc.getName();
    JFrame jf = new JFrame("Weka Classifier Visualize: " + plotName);
    jf.setSize(500, 400);
    jf.getContentPane().setLayout(new BorderLayout());
    jf.getContentPane().add(vmc, BorderLayout.CENTER);
    jf.setVisible(true);
}

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