Class ClassifierErrorsPlotInstances

java.lang.Object
weka.gui.explorer.AbstractPlotInstances
weka.gui.explorer.ClassifierErrorsPlotInstances
All Implemented Interfaces:
Serializable, OptionHandler

public class ClassifierErrorsPlotInstances extends AbstractPlotInstances
A class for generating plottable visualization errors.

Example usage:

 Instances train = ... // from somewhere
 Instances test = ... // from somewhere
 Classifier cls = ... // from somewhere
 // build classifier
 cls.buildClassifier(train);
 // evaluate classifier and generate plot instances
 ClassifierPlotInstances plotInstances = new ClassifierPlotInstances();
 plotInstances.setClassifier(cls);
 plotInstances.setInstances(train);
 plotInstances.setClassIndex(train.classIndex());
 plotInstances.setUp();
 Evaluation eval = new Evaluation(train);
 for (int i = 0; i < test.numInstances(); i++)
   plotInstances.process(test.instance(i), cls, eval);
 // generate visualization
 VisualizePanel visPanel = new VisualizePanel();
 visPanel.addPlot(plotInstances.getPlotData("plot name"));
 visPanel.setColourIndex(plotInstances.getPlotInstances().classIndex()+1);
 // clean up
 plotInstances.cleanUp();
 
Version:
$Revision: 10220 $
Author:
fracpete (fracpete at waikato dot ac dot nz)
See Also:
  • Constructor Details

    • ClassifierErrorsPlotInstances

      public ClassifierErrorsPlotInstances()
  • Method Details

    • getPlotShapes

      public ArrayList<Integer> getPlotShapes()
      Get the vector of plot shapes (see weka.gui.visualize.Plot2D).
      Returns:
      the vector of plot shapes.
    • getPlotSizes

      public ArrayList<Object> getPlotSizes()
      Get the vector of plot sizes (see weka.gui.visualize.Plot2D).
      Returns:
      the vector of plot sizes.
    • setPlotShapes

      public void setPlotShapes(ArrayList<Integer> plotShapes)
      Set the vector of plot shapes to use;
      Parameters:
      plotShapes -
    • setPlotSizes

      public void setPlotSizes(ArrayList<Object> plotSizes)
      Set the vector of plot sizes to use
      Parameters:
      plotSizes - the plot sizes to use
    • setClassifier

      public void setClassifier(Classifier value)
      Sets the classifier used for making the predictions.
      Parameters:
      value - the classifier to use
    • getClassifier

      public Classifier getClassifier()
      Returns the currently set classifier.
      Returns:
      the classifier in use
    • setClassIndex

      public void setClassIndex(int index)
      Sets the 0-based class index.
      Parameters:
      index - the class index
    • getClassIndex

      public int getClassIndex()
      Returns the 0-based class index.
      Returns:
      the class index
    • setEvaluation

      public void setEvaluation(Evaluation value)
      Sets the Evaluation object to use.
      Parameters:
      value - the evaluation to use
    • getEvaluation

      public Evaluation getEvaluation()
      Returns the Evaluation object in use.
      Returns:
      the evaluation object
    • setSaveForVisualization

      public void setSaveForVisualization(boolean value)
      Sets whether the instances are saved for visualization or only evaluation of the prediction is to happen.
      Parameters:
      value - if true then the instances will be saved
    • getSaveForVisualization

      public boolean getSaveForVisualization()
      Returns whether the instances are saved for visualization for only evaluation of the prediction is to happen.
      Returns:
      true if the instances are saved
    • setPointSizeProportionalToMargin

      public void setPointSizeProportionalToMargin(boolean b)
      Set whether the point size should be proportional to the prediction margin (classification only).
      Parameters:
      b - true if the point size should be proportional to the margin
    • getPointSizeProportionalToMargin

      public boolean getPointSizeProportionalToMargin()
      Get whether the point size should be proportional to the prediction margin (classification only).
      Returns:
      true if the point size should be proportional to the margin
    • process

      public void process(Instances batch, double[][] predictions, Evaluation eval)
    • process

      public void process(Instance toPredict, Classifier classifier, Evaluation eval)
      Process a classifier's prediction for an instance and update a set of plotting instances and additional plotting info. m_PlotShape for nominal class datasets holds shape types (actual data points have automatic shape type assignment; classifier error data points have box shape type). For numeric class datasets, the actual data points are stored in m_PlotInstances and m_PlotSize stores the error (which is later converted to shape size values).
      Parameters:
      toPredict - the actual data point
      classifier - the classifier
      eval - the evaluation object to use for evaluating the classifier on the instance to predict
      See Also:
      • m_PlotShapes
      • m_PlotSizes
      • AbstractPlotInstances.m_PlotInstances
    • cleanUp

      public void cleanUp()
      For freeing up memory. Plot data cannot be generated after this call!
      Overrides:
      cleanUp in class AbstractPlotInstances