PRTools Contents

PRTools User Guide



Percentile combining classifier

    W = PERC(V,P)
    W = V*PERC([],P)

 V Set of classifiers
 P Percentile, 0 <= P <= 100

 W Percentile combining classifier on V


If V = [V1,V2,V3, ... ] is a set of classifiers trained on the  same classes and W is the percentile combiner: it selects the class  defined by the percentile of the outputs of the input classifiers. This  might also be used as A*[V1,V2,V3]*PERC([],P) in which A is a dataset to  be classified.

 PERC([],0) is equal to MINC
 PERC([],50) is equal to MEDIANC
 PERC([],100) is equal to MAXC

If it is desired to operate on posterior probabilities then the  input classifiers should be extended like V = V*CLASSC;

The base classifiers may be combined in a stacked way (operating  in the same feature space by V = [V1,V2,V3, ... ] or in a parallel  way (operating in different feature spaces) by V = [V1;V2;V3; ... ]

See also

mappings, datasets, votec, maxc, minc, meanc, medianc, prodc, averagec, stacked, parallel,



PRTools Contents

PRTools User Guide

This file has been automatically generated. If badly readable, use the help-command in Matlab.