have proposed a sweeping generalization of the entire probabilistic
neural network paradigm. They estimate the underlying probability
density functions based on the Gram-Charlier series expansion, with
optional use of Parzen windows. Significantly improved performance
is claimed.
A Sample Program
This section offers a subroutine for classifying using the probabilistic
neural network (Parzen-Bayes classifier). A subroutine for automati-
cally choosing an optimal value for the scaling parameter σ is also
given.
int pnn (
int nvars , // Number of
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