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Classifier evaluation (learning curve), bootstrap version


 A Training dataset
 CLASSF Classifier to evaluate
 TRAINSIZES Vector of class sizes, used to generate subsets of A (default [2,3,5,7,10,15,20,30,50,70,100])
 NREPS Number of repetitions (default 1)

 E Error structure (see PLOTE)


Generates at random, for all class sizes defined in TRAINSIZES, training  sets out of the dataset A and uses these for training the untrained  classifier CLASSF. CLASSF may also be a cell array of untrained  classifiers; in this case the routine will be run for all of them. The  resulting trained classifiers are tested on all objects in A. This  procedure is then repeated N times.

Training set generation is done "with replacement" and such that for each  run the larger training sets include the smaller ones and that for all  classifiers the same training sets are used.

If CLASSF is fully deterministic, this function uses the RAND random  generator and thereby reproduces if its seed is reset (see RAND).  If CLASSF uses RANDN, its seed may have to be set as well.



See also

mappings, datasets, clevalb, testc, plote,

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PRTools User Guide

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