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Construction of a rejecting classifier


 A Dataset
 W Trained or untrained classifier
 FRAC Fraction to be rejected. Default: 0.05
 TYPE String with reject type: 'ambiguity' or 'outlier'.  'a' and 'o' are supported as well. Default is 'a'.

 WR Rejecting classifier


 a = gendatb
 w = ldc(a);
 v = rejectc(a,w,0.2);


This command extends an arbitrary classifier with a reject option. If WR is used for classifying a dataset B, then D = B*WR has C+1 columns  ('features'), one for every class in A and an additional one that takes  care of the rejection: a NaN for numeric labels (classnames in A) or en  empty string for string labels.  NOTE: Objects that are rejected are not counted as an error in TESTC. The  classification error estimated by TESTC just considers the total number  of objects for wich B*WR*LABELD has a correct classname and neglects all  others. So by rejection the error estimate by TESTC may increase,  decrease or stay equal.

See also

datasets, mappings, labeld, testc, rejectm,

PRTools Contents

PRTools User Guide

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