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PRTools User Guide



Force density based classifiers to use log-densities

    V = LOGDENS(W)

 W Density based trained classifier

 V Log-density based trained classifier


Density based classifiers suffer from a low numeric accuracy in the tails  of the distributions. Especially for overtrained or high dimensional  classifiers this may cause zero-density estimates for many test samples,  resulting in a bad performance. This can be avoided by computing  log-densities offered by this routine. This works for all classifiers  based on normal distributions (e.g. LDC, QDC, MOGC) and Parzen estimates  (PARZENC, PARZENDC). The computation of log-densities is , in order to be

effective, combined with a normalisation, resulting in posterior
distributions. As a consequence, the possibility to output densities is

See also

mappings, ldc, udc, qdc, mogc, parzenc, parzendc, normal_map, parzen_map, classc,

PRTools Contents

PRTools User Guide

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