Feature selection for best mean square approximation of class densities

摘要

A criterion for feature selection is proposed which is based on mean square approximation of class density functions. It is shown that for the widest possible class of approximants, the criterion reduces to Devijer's Bayesian distance. For linear approximants the criterion is equivalent to well known generalized Fisher criteria.