Description: BAYESGAUSS Bayes classifier for Gaussian patterns.
D = BAYESGAUSS(X, CA, MA, P) computes the Bayes decision
functions of the n-dimensional patterns in the rows of X.
CA is an array of size n-by-n-by-W containing W covariance
matrices of size n-by-n, where W is the number of classes.
MA is an array of size n-by-W, whose columns are the corres-
ponding mean vectors. A cov. matrix and a mean vector must be
specified for each class, even if some are equal. X is of size
K-by-n, where K is the number of patterns to be classified. P is
a 1-by-W array, containing the probabilities of occurrence of
each class. If P is not included in the argument, the classes
are assumed to be equally likely.
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bayesgauss.m
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