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Class weka.classifiers.evaluation.MarginCurve
java.lang.Object
|
+----weka.classifiers.evaluation.MarginCurve
- public class MarginCurve
- extends java.lang.Object
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: 1.5 $
- Author:
- Len Trigg (len@intelligenesis.net)
MarginCurve()
-
getCurve(FastVector)
- Calculates the cumulative margin distribution for the set of
predictions, returning the result as a set of Instances.
main(String[])
- Tests the MarginCurve generation from the command line.
MarginCurve
public MarginCurve()
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.
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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