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Clean dataset for small class size behavior of classifiers


 A Dataset
 N Minimum desired class size, default 1
 U Untrained fallback classifier, default ONEC

 B Dataset with small and empty classes removed
 M Number of objects in B
 K Feature size of B
 C Number of classes in B
 LABLIST Label list of A
 L Classes of A still availiable in B
 W Trained fallback classifier


This routine serves three purposes

  • It summarises a number of statements in the training parts of a  classifier in orer to make the source more readable.
  • Removal of small classes.
  • In case B does not contain at least two classes of the desired sample  size, the fallback classifier U is trained by A and returned in W.

This routine takes facilitates the handling of imcomplete training sets,  together with the support routines ONEC, ALLCLASS and, CLASSUSE.

See also

datasets, mappings, onec, allclass, classuse,

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PRTools User Guide

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