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Suppose we have training data from the Gaussian distribution of known covariance S but unknown mean Mu. Suppose further that this mean itself is random, and characterized by Gaussian density having mean Mu0 and covariance S0. Explain the MAP (maximum a posteriori) estimator for the Mu?

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Computer Engineering, Engineering

Category:- Computer Engineering
Reference No.:- M9171054

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