Example usage for weka.classifiers.evaluation ThresholdCurve FP_RATE_NAME

Introduction

In this page you can find the example usage for weka.classifiers.evaluation ThresholdCurve FP_RATE_NAME.

Prototype

String FP_RATE_NAME

To view the source code for weka.classifiers.evaluation ThresholdCurve FP_RATE_NAME.

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Document

attribute name: False Positive Rate"

Usage

From source file:bme.mace.logicdomain.Evaluation.java

License:Open Source License

/**
 * Returns the area under ROC for those predictions that have been collected
 * in the evaluateClassifier(Classifier, Instances) method. Returns
 * Instance.missingValue() if the area is not available.
 * /*from  w  ww. j  a va2 s  . co m*/
 * @param classIndex the index of the class to consider as "positive"
 * @return the area under the ROC curve or not a number
 */
public double areaUnderROC(int classIndex) {

    // Check if any predictions have been collected
    if (m_Predictions == null) {
        return Instance.missingValue();
    } else {
        ThresholdCurve tc = new ThresholdCurve();
        Instances result = tc.getCurve(m_Predictions, classIndex);
        double rocArea = ThresholdCurve.getROCArea(result);
        if (rocArea < 0.5) {
            rocArea = 1 - rocArea;
        }

        int tpIndex = result.attribute(ThresholdCurve.TP_RATE_NAME).index();
        int fpIndex = result.attribute(ThresholdCurve.FP_RATE_NAME).index();
        double[] tpRate = result.attributeToDoubleArray(tpIndex);
        double[] fpRate = result.attributeToDoubleArray(fpIndex);

        try {
            FileWriter fw;
            if (classIndex == 0)
                fw = new FileWriter("C://1.csv", true);
            else
                fw = new FileWriter("C://1.csv", true);

            BufferedWriter bw = new BufferedWriter(fw);
            int length = fpRate.length;
            for (int i = 255; i >= 0; i--) {

                int index = i * (length - 1) / 255;
                bw.write(fpRate[index] + ",");
            }
            bw.write("\n");
            for (int i = 255; i >= 0; i--) {
                int index = i * (length - 1) / 255;
                bw.write(tpRate[index] + ",");
            }
            bw.write("\n");

            bw.close();
            fw.close();
        } catch (IOException e) {
            // TODO Auto-generated catch block
            e.printStackTrace();
        }

        return rocArea;
    }
}

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From source file:meka.gui.explorer.classify.ShowROC.java

License:Open Source License

/**
 * Returns the name of the default X column to display.
 *
 * @return              the name of the column
 *//*w  ww .  j  a  v a 2 s.c om*/
protected String getDefaultXColumn() {
    return ThresholdCurve.FP_RATE_NAME;
}

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From source file:meka.gui.guichooser.ROC.java

License:Open Source License

/**
 * Called by the menu items action listener.
 *//* w w w.  ja  va2  s  .c  o  m*/
@Override
protected void launch() {
    m_FileChooser = GUIHelper.newConverterFileChooser();
    // choose file
    int retVal = m_FileChooser.showOpenDialog(null);
    if (retVal != JFileChooser.APPROVE_OPTION)
        return;
    File file = m_FileChooser.getSelectedFile();

    // create plot
    Instances data;
    try {
        data = m_FileChooser.getLoader().getDataSet();
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Error loading file '" + file + "':\n" + e, "Error",
                JOptionPane.ERROR_MESSAGE);
        e.printStackTrace();
        return;
    }
    data.setClassIndex(data.numAttributes() - 1);
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setROCString("(Area under ROC = " + Utils.doubleToString(ThresholdCurve.getROCArea(data), 4) + ")");
    vmc.setName(data.relationName());
    PlotData2D tempd = new PlotData2D(data);
    tempd.setPlotName(data.relationName());
    tempd.m_displayAllPoints = true;
    // specify which points are connected
    boolean[] cp = new boolean[data.numInstances()];
    for (int n = 1; n < cp.length; n++)
        cp[n] = true;
    try {
        tempd.setConnectPoints(cp);
        vmc.addPlot(tempd);
        if (data.attribute(ThresholdCurve.FP_RATE_NAME) != null)
            vmc.setXIndex(data.attribute(ThresholdCurve.FP_RATE_NAME).index());
        if (data.attribute(ThresholdCurve.TP_RATE_NAME) != null)
            vmc.setYIndex(data.attribute(ThresholdCurve.TP_RATE_NAME).index());
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Error adding plot:\n" + e, "Error", JOptionPane.ERROR_MESSAGE);
        e.printStackTrace();
        return;
    }

    MekaFrame frame = new MekaFrame();
    frame.setTitle(getName());
    frame.setDefaultCloseOperation(MekaFrame.DISPOSE_ON_CLOSE);
    frame.getContentPane().setLayout(new BorderLayout());
    frame.getContentPane().add(vmc);
    frame.setSize(800, 600);
    frame.setLocationRelativeTo(null);
    frame.setVisible(true);
}

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