Machine Learning, Clustering, Expectation Maximization, Gaussian Mixture Model, Image Clustering.
iterates between E and M step until it converges where: E- step: assign cluster responsibilities, given current parameters M-step: Update parameters, given current cluster responsibilities Let’s talk about its implementation in more detail. Let’s remember why GMM is used for. Unlike k- mean it does