Steps of EM algorithm(3) each data point now associate with (r n,1, r n,2,…, r n,k ) r n,k – how likely they belong to k th mixture, 0<r<1 using r, compute weighted mean and variance for each gaussian model We get new Ѳ, set it as the new parameter and iterate the process (find new r -> new Ѳ -> ……) Consist of expectation step and maximization step
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