4.9 ( ) www Consider a generative classification model for K classes defined by prior class probabilities
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4.9 () www Consider a generative classification model for K classes defined by prior class probabilities p(Ck) = πk and general class-conditional densities p(φ|Ck)
where φ is the input feature vector. Suppose we are given a training data set {φn, tn}
where n = 1, . . . , N, and tn is a binary target vector of length K that uses the 1-of-
K coding scheme, so that it has components tnj = Ijk if pattern n is from class Ck.
Assuming that the data points are drawn independently from this model, show that the maximum-likelihood solution for the prior probabilities is given by
πk = Nk N
(4.159)
where Nk is the number of data points assigned to class Ck.
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Related Book For
Pattern Recognition And Machine Learning
ISBN: 9780387310732
1st Edition
Authors: Christopher M Bishop
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