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5586 Pattern Recognition (3) Decision functions, distance measures, minimum distance classifiers, hard clustering methods, fuzzy clustering methods, statistical pattern recognition methods, Bayesian classifiers, error probabilities, estimation of density functions, perceptrons, least-mean-square algorithms, feature selection, dimensionality reduction and syntactic pattern recognition. Prerequisites: CS 394R or MATH 436, course in high-level programming language, some matrix theory and linear algebra or instructor's consent.
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