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.

bayesgauss.m

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