Examples of weka.classifiers.evaluation.MarginCurve

weka.classifiers.evaluation.MarginCurve
Generates points illustrating the prediction margin. The margin is defined as the difference between the probability predicted for the actual class and the highest probability predicted for the other classes. One hypothesis as to the good performance of boosting algorithms is that they increaes the margins on the training data and this gives better performance on test data. @author Len Trigg (len@reeltwo.com) @version $Revision: 1.11 $

    JMenuItem visMargin = new JMenuItem("Visualize margin curve");
    if ((preds != null) && (classAtt != null) && (classAtt.isNominal())) {
      visMargin.addActionListener(new ActionListener() {
    public void actionPerformed(ActionEvent e) {
      try {
        MarginCurve tc = new MarginCurve();
        Instances result = tc.getCurve(preds);
        VisualizePanel vmc = new VisualizePanel();
        vmc.setName(result.relationName());
        vmc.setLog(m_Log);
        PlotData2D tempd = new PlotData2D(result);
        tempd.setPlotName(result.relationName());
        tempd.addInstanceNumberAttribute();
        vmc.addPlot(tempd);
        visualizeClassifierErrors(vmc);
      } catch (Exception ex) {
        ex.printStackTrace();
      }
    }
  });
    } else {
      visMargin.setEnabled(false);
    }
    resultListMenu.add(visMargin);


    JMenu visThreshold = new JMenu("Visualize threshold curve");
    if ((preds != null) && (classAtt != null) && (classAtt.isNominal())) {
      for (int i = 0; i < classAtt.numValues(); i++) {
  JMenuItem clv = new JMenuItem(classAtt.value(i));
  final int classValue = i;
  clv.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        try {
    ThresholdCurve tc = new ThresholdCurve();
    Instances result = tc.getCurve(preds, classValue);
    //VisualizePanel vmc = new VisualizePanel();
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setROCString("(Area under ROC = " + 
         Utils.doubleToString(ThresholdCurve.getROCArea(result), 4) + ")");
    vmc.setLog(m_Log);
    vmc.setName(result.relationName()+". (Class value "+
          classAtt.value(classValue)+")");
    PlotData2D tempd = new PlotData2D(result);
    tempd.setPlotName(result.relationName());
    tempd.addInstanceNumberAttribute();
    // specify which points are connected
    boolean[] cp = new boolean[result.numInstances()];
    for (int n = 1; n < cp.length; n++)
      cp[n] = true;
    tempd.setConnectPoints(cp);
    // add plot
    vmc.addPlot(tempd);
    visualizeClassifierErrors(vmc);
        } catch (Exception ex) {
    ex.printStackTrace();
        }
        }
    });
    visThreshold.add(clv);
      }
    } else {
      visThreshold.setEnabled(false);
    }
    resultListMenu.add(visThreshold);
    
    JMenu visCostBenefit = new JMenu("Cost/Benefit analysis");
    if ((preds != null) && (classAtt != null) && (classAtt.isNominal())) {
      for (int i = 0; i < classAtt.numValues(); i++) {
        JMenuItem clv = new JMenuItem(classAtt.value(i));
        final int classValue = i;
        clv.addActionListener(new ActionListener() {
            public void actionPerformed(ActionEvent e) {
              try {
                ThresholdCurve tc = new ThresholdCurve();
                Instances result = tc.getCurve(preds, classValue);


                // Create a dummy class attribute with the chosen
                // class value as index 0 (if necessary).
                Attribute classAttToUse = classAtt;
                if (classValue != 0) {

View Full Code Here

    JMenuItem visMargin = new JMenuItem(Messages.getInstance().getString("ClassifierPanel_Visualize_VisMargin_JMenuItem_Text"));
    if (preds != null) {
      visMargin.addActionListener(new ActionListener() {
    public void actionPerformed(ActionEvent e) {
      try {
        MarginCurve tc = new MarginCurve();
        Instances result = tc.getCurve(preds);
        VisualizePanel vmc = new VisualizePanel();
        vmc.setName(result.relationName());
        vmc.setLog(m_Log);
        PlotData2D tempd = new PlotData2D(result);
        tempd.setPlotName(result.relationName());
        tempd.addInstanceNumberAttribute();
        vmc.addPlot(tempd);
        visualizeClassifierErrors(vmc);
      } catch (Exception ex) {
        ex.printStackTrace();
      }
    }
  });
    } else {
      visMargin.setEnabled(false);
    }
    resultListMenu.add(visMargin);


    JMenu visThreshold = new JMenu(Messages.getInstance().getString("ClassifierPanel_Visualize_VisThreshold_JMenu_Text"));
    if (preds != null && classAtt != null) {
      for (int i = 0; i < classAtt.numValues(); i++) {
  JMenuItem clv = new JMenuItem(classAtt.value(i));
  final int classValue = i;
  clv.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        try {
    ThresholdCurve tc = new ThresholdCurve();
    Instances result = tc.getCurve(preds, classValue);
    //VisualizePanel vmc = new VisualizePanel();
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setROCString(Messages.getInstance().getString("ClassifierPanel_Visualize_VMC_SetROCString_Text_First") + 
         Utils.doubleToString(ThresholdCurve.getROCArea(result), 4) + Messages.getInstance().getString("ClassifierPanel_Visualize_VMC_SetROCString_Text_Second"));
    vmc.setLog(m_Log);
    vmc.setName(result.relationName()+Messages.getInstance().getString("ClassifierPanel_Visualize_VMC_SetName_Text_First") +
          classAtt.value(classValue) + Messages.getInstance().getString("ClassifierPanel_Visualize_VMC_SetName_Text_Second"));
    PlotData2D tempd = new PlotData2D(result);
    tempd.setPlotName(result.relationName());
    tempd.addInstanceNumberAttribute();
    // specify which points are connected
    boolean[] cp = new boolean[result.numInstances()];
    for (int n = 1; n < cp.length; n++)
      cp[n] = true;
    tempd.setConnectPoints(cp);
    // add plot
    vmc.addPlot(tempd);
    visualizeClassifierErrors(vmc);
        } catch (Exception ex) {
    ex.printStackTrace();
        }
        }
    });
    visThreshold.add(clv);
      }
    } else {
      visThreshold.setEnabled(false);
    }
    resultListMenu.add(visThreshold);
    
    JMenu visCostBenefit = new JMenu(Messages.getInstance().getString("ClassifierPanel_Visualize_VisCostBenefit_JMenu_Text"));
    if ((preds != null) && (classAtt != null) && (classAtt.isNominal())) {
      for (int i = 0; i < classAtt.numValues(); i++) {
        JMenuItem clv = new JMenuItem(classAtt.value(i));
        final int classValue = i;
        clv.addActionListener(new ActionListener() {
            public void actionPerformed(ActionEvent e) {
              try {
                ThresholdCurve tc = new ThresholdCurve();
                Instances result = tc.getCurve(preds, classValue);


                // Create a dummy class attribute with the chosen
                // class value as index 0 (if necessary).
                Attribute classAttToUse = classAtt;
                if (classValue != 0) {

View Full Code Here

    JMenuItem visMargin = new JMenuItem("Visualize margin curve");
    if (preds != null) {
      visMargin.addActionListener(new ActionListener() {
    public void actionPerformed(ActionEvent e) {
      try {
        MarginCurve tc = new MarginCurve();
        Instances result = tc.getCurve(preds);
        VisualizePanel vmc = new VisualizePanel();
        vmc.setName(result.relationName());
        vmc.setLog(m_Log);
        PlotData2D tempd = new PlotData2D(result);
        tempd.setPlotName(result.relationName());
        tempd.addInstanceNumberAttribute();
        vmc.addPlot(tempd);
        visualizeClassifierErrors(vmc);
      } catch (Exception ex) {
        ex.printStackTrace();
      }
    }
  });
    } else {
      visMargin.setEnabled(false);
    }
    resultListMenu.add(visMargin);


    JMenu visThreshold = new JMenu("Visualize threshold curve");
    if (preds != null && classAtt != null) {
      for (int i = 0; i < classAtt.numValues(); i++) {
  JMenuItem clv = new JMenuItem(classAtt.value(i));
  final int classValue = i;
  clv.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        try {
    ThresholdCurve tc = new ThresholdCurve();
    Instances result = tc.getCurve(preds, classValue);
    //VisualizePanel vmc = new VisualizePanel();
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setROCString("(Area under ROC = " + 
         Utils.doubleToString(ThresholdCurve.getROCArea(result), 4) + ")");
    vmc.setLog(m_Log);

View Full Code Here

    JMenuItem visMargin = new JMenuItem("Visualize margin curve");
    if ((preds != null) && (classAtt != null) && (classAtt.isNominal())) {
      visMargin.addActionListener(new ActionListener() {
    public void actionPerformed(ActionEvent e) {
      try {
        MarginCurve tc = new MarginCurve();
        Instances result = tc.getCurve(preds);
        VisualizePanel vmc = new VisualizePanel();
        vmc.setName(result.relationName());
        vmc.setLog(m_Log);
        PlotData2D tempd = new PlotData2D(result);
        tempd.setPlotName(result.relationName());
        tempd.addInstanceNumberAttribute();
        vmc.addPlot(tempd);
        visualizeClassifierErrors(vmc);
      } catch (Exception ex) {
        ex.printStackTrace();
      }
    }
  });
    } else {
      visMargin.setEnabled(false);
    }
    resultListMenu.add(visMargin);


    JMenu visThreshold = new JMenu("Visualize threshold curve");
    if ((preds != null) && (classAtt != null) && (classAtt.isNominal())) {
      for (int i = 0; i < classAtt.numValues(); i++) {
  JMenuItem clv = new JMenuItem(classAtt.value(i));
  final int classValue = i;
  clv.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        try {
    ThresholdCurve tc = new ThresholdCurve();
    Instances result = tc.getCurve(preds, classValue);
    //VisualizePanel vmc = new VisualizePanel();
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setROCString("(Area under ROC = " + 
         Utils.doubleToString(ThresholdCurve.getROCArea(result), 4) + ")");
    vmc.setLog(m_Log);
    vmc.setName(result.relationName()+". (Class value "+
          classAtt.value(classValue)+")");
    PlotData2D tempd = new PlotData2D(result);
    tempd.setPlotName(result.relationName());
    tempd.addInstanceNumberAttribute();
    // specify which points are connected
    boolean[] cp = new boolean[result.numInstances()];
    for (int n = 1; n < cp.length; n++)
      cp[n] = true;
    tempd.setConnectPoints(cp);
    // add plot
    vmc.addPlot(tempd);
    visualizeClassifierErrors(vmc);
        } catch (Exception ex) {
    ex.printStackTrace();
        }
        }
    });
    visThreshold.add(clv);
      }
    } else {
      visThreshold.setEnabled(false);
    }
    resultListMenu.add(visThreshold);
    
    JMenu visCostBenefit = new JMenu("Cost/Benefit analysis");
    if ((preds != null) && (classAtt != null) && (classAtt.isNominal())) {
      for (int i = 0; i < classAtt.numValues(); i++) {
        JMenuItem clv = new JMenuItem(classAtt.value(i));
        final int classValue = i;
        clv.addActionListener(new ActionListener() {
            public void actionPerformed(ActionEvent e) {
              try {
                ThresholdCurve tc = new ThresholdCurve();
                Instances result = tc.getCurve(preds, classValue);


                // Create a dummy class attribute with the chosen
                // class value as index 0 (if necessary).
                Attribute classAttToUse = classAtt;
                if (classValue != 0) {

View Full Code Here

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weka.core.Attribute

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weka.core.FastVector

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