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For questions related to maximum likelihood estimation (MLE), which is a frequentist approach for estimating the parameters of an assumed probability distribution given some observed data. This is done by maximizing a likelihood function so that, under the assumed statistical model, the observed data is most probable. The resulting estimate is known as the maximum likelihood estimate.

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Likelihood function for Gaussian Discriminant Analsis

Im trying to understand how the likelhood function for gaussian discriminant analysis is derived. I self studying Murphy's Probabilistic Machine learning, and in it, he states the likelihood function …
turtle_in_mind's user avatar