Machine Learning, Clustering, Data Science, Unsupervised Learning, Towards Data Science.
the model parameter was correct, this expected likelihood will be the actual likelihood of our observed data; if the parameters were not correct, it will just be a lower bound. M-step: Now that we’ve got an expected likelihood function with no unobserved variables in it, maximize the function as