Package weka.classifiers.evaluation
Class MarginCurve
- java.lang.Object
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- weka.classifiers.evaluation.MarginCurve
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- All Implemented Interfaces:
RevisionHandler
public class MarginCurve extends java.lang.Object implements RevisionHandler
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.- Version:
- $Revision: 1.11 $
- Author:
- Len Trigg (len@reeltwo.com)
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Constructor Summary
Constructors Constructor Description MarginCurve()
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description Instances
getCurve(FastVector predictions)
Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances.java.lang.String
getRevision()
Returns the revision string.static void
main(java.lang.String[] args)
Tests the MarginCurve generation from the command line.
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Method Detail
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getCurve
public Instances getCurve(FastVector predictions)
Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances. The structure of these Instances is as follows:- Margin contains the margin value (which should be plotted as an x-coordinate)
- Current contains the count of instances with the current margin (plot as y axis)
- Cumulative contains the count of instances with margin less than or equal to the current margin (plot as y axis)
- Returns:
- datapoints as a set of instances, null if no predictions have been made.
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getRevision
public java.lang.String getRevision()
Returns the revision string.- Specified by:
getRevision
in interfaceRevisionHandler
- Returns:
- the revision
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main
public static void main(java.lang.String[] args)
Tests the MarginCurve generation from the command line. The classifier is currently hardcoded. Pipe in an arff file.- Parameters:
args
- currently ignored
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