Technical Details about the Expectation Maximization (EM) Algorithm
نویسنده
چکیده
P(X|θ) is the (observable) data likelihood. The parameter θ is omitted sometimes for simple notation. MLE is normally done by taking the derivative of the data likelihood P(X) with respect to the model parameter θ and solving the equation. However, in some cases where we have hidden (unobserved) variables in the model, the derivative w.r.t. the model parameter does not have a close form solution. We will illustrate this problem with a simple example of mixture model with hidden variables.
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