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This Manual is for the sole use of designated educators and must not be distributed to students except in short, isolated portions and in conjunction with the use of Pattern Classification (2nd ed.) June 18, 2003 Preface In writing this Solution Manual I have learned a very important lesson.

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( 3.7) The decision space is then based on a comparison of the probability density estimate per class and the prior probabilities [Parzen, 1962, Duda et al., 2012, given here as Equation 3.8,f The ...

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Pattern Classification, Chapter 3 4 Parameters in ML estimation are fixed but unknown! Bayesian parameter estimation procedure, by its nature, utilizes whatever prior information is available about the unknown parameter MLE: Best parameters are obtained by maximizing the probability of obtaining the samples observed

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