Example usage for weka.gui.visualize VisualizePanel setXIndex

Introduction

In this page you can find the example usage for weka.gui.visualize VisualizePanel setXIndex.

Prototype

public void setXIndex(int index) throws Exception 

Source Link

Document

Set the index of the attribute for the x axis

Usage

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

License:Open Source License

/**
 * Creates a panel displaying the data.//ww  w.  j av a  2  s .  c o m
 *
 * @param data          the plot data
 * @return              the panel
 * @throws Exception    if plot generation fails
 */
protected VisualizePanel createPanel(Instances data) throws Exception {
    VisualizePanel result = new ThresholdVisualizePanel();
    PlotData2D plot = new PlotData2D(data);
    plot.setPlotName("Incremental performance");
    plot.m_displayAllPoints = true;
    boolean[] connectPoints = new boolean[data.numInstances()];
    for (int cp = 1; cp < connectPoints.length; cp++)
        connectPoints[cp] = true;
    plot.setConnectPoints(connectPoints);
    result.addPlot(plot);
    if (data.attribute(SAMPLES) != null)
        result.setXIndex(data.attribute(SAMPLES).index());
    if (data.attribute(ACCURACY) != null)
        result.setYIndex(data.attribute(ACCURACY).index());
    return result;
}

---

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

License:Open Source License

/**
 * Creates a panel displaying the data.//from w  w  w.  j ava2  s .c  o  m
 *
 * @param data          the plot data
 * @return              the panel
 * @throws Exception    if plot generation fails
 */
protected VisualizePanel createPanel(Instances data) throws Exception {
    VisualizePanel result = new ThresholdVisualizePanel();
    PlotData2D plot = new PlotData2D(data);
    plot.setPlotName("Macro-averaged Performance");
    plot.m_displayAllPoints = true;
    boolean[] connectPoints = new boolean[data.numInstances()];
    for (int cp = 1; cp < connectPoints.length; cp++)
        connectPoints[cp] = true;
    plot.setConnectPoints(connectPoints);
    result.addPlot(plot);
    if (data.attribute(SAMPLES) != null)
        result.setXIndex(data.attribute(SAMPLES).index());
    if (data.attribute(ACCURACY) != null)
        result.setYIndex(data.attribute(ACCURACY).index());
    return result;
}

---

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

License:Open Source License

/**
 * Creates a panel displaying the data./*  w w  w . j  ava2  s.c o  m*/
 *
 * @param data          the plot data
 * @return              the panel
 * @throws Exception    if plot generation fails
 */
protected VisualizePanel createPanel(Instances data) throws Exception {
    VisualizePanel result = new ThresholdVisualizePanel();
    PlotData2D plot = new PlotData2D(data);
    plot.setPlotName("Micro-averaged Performance");
    plot.m_displayAllPoints = true;
    boolean[] connectPoints = new boolean[data.numInstances()];
    for (int cp = 1; cp < connectPoints.length; cp++)
        connectPoints[cp] = true;
    plot.setConnectPoints(connectPoints);
    result.addPlot(plot);
    if (data.attribute(SAMPLES) != null)
        result.setXIndex(data.attribute(SAMPLES).index());
    if (data.attribute(ACCURACY) != null)
        result.setYIndex(data.attribute(ACCURACY).index());
    return result;
}

---