Package weka.gui.explorer
Class ClassifierErrorsPlotInstances
java.lang.Object
weka.gui.explorer.AbstractPlotInstances
weka.gui.explorer.ClassifierErrorsPlotInstances
- All Implemented Interfaces:
Serializable,OptionHandler
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:
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionvoidcleanUp()For freeing up memory.Returns the currently set classifier.intReturns the 0-based class index.Returns the Evaluation object in use.Get the vector of plot shapes (see weka.gui.visualize.Plot2D).Get the vector of plot sizes (see weka.gui.visualize.Plot2D).booleanGet whether the point size should be proportional to the prediction margin (classification only).booleanReturns whether the instances are saved for visualization for only evaluation of the prediction is to happen.voidprocess(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.voidprocess(Instances batch, double[][] predictions, Evaluation eval) voidsetClassifier(Classifier value) Sets the classifier used for making the predictions.voidsetClassIndex(int index) Sets the 0-based class index.voidsetEvaluation(Evaluation value) Sets the Evaluation object to use.voidsetPlotShapes(ArrayList<Integer> plotShapes) Set the vector of plot shapes to use;voidsetPlotSizes(ArrayList<Object> plotSizes) Set the vector of plot sizes to usevoidsetPointSizeProportionalToMargin(boolean b) Set whether the point size should be proportional to the prediction margin (classification only).voidsetSaveForVisualization(boolean value) Sets whether the instances are saved for visualization or only evaluation of the prediction is to happen.Methods inherited from class weka.gui.explorer.AbstractPlotInstances
canPlot, getInstances, getOptions, getPlotData, getPlotInstances, listOptions, setInstances, setOptions, setUp
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Constructor Details
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ClassifierErrorsPlotInstances
public ClassifierErrorsPlotInstances()
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Method Details
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getPlotShapes
Get the vector of plot shapes (see weka.gui.visualize.Plot2D).- Returns:
- the vector of plot shapes.
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getPlotSizes
Get the vector of plot sizes (see weka.gui.visualize.Plot2D).- Returns:
- the vector of plot sizes.
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setPlotShapes
Set the vector of plot shapes to use;- Parameters:
plotShapes-
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setPlotSizes
Set the vector of plot sizes to use- Parameters:
plotSizes- the plot sizes to use
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setClassifier
Sets the classifier used for making the predictions.- Parameters:
value- the classifier to use
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getClassifier
Returns the currently set classifier.- Returns:
- the classifier in use
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setClassIndex
public void setClassIndex(int index) Sets the 0-based class index.- Parameters:
index- the class index
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getClassIndex
public int getClassIndex()Returns the 0-based class index.- Returns:
- the class index
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setEvaluation
Sets the Evaluation object to use.- Parameters:
value- the evaluation to use
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getEvaluation
Returns the Evaluation object in use.- Returns:
- the evaluation object
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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
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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
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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
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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
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process
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process
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 pointclassifier- the classifiereval- the evaluation object to use for evaluating the classifier on the instance to predict- See Also:
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m_PlotShapesm_PlotSizesAbstractPlotInstances.m_PlotInstances
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cleanUp
public void cleanUp()For freeing up memory. Plot data cannot be generated after this call!- Overrides:
cleanUpin classAbstractPlotInstances
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