Machine Learning, Clustering, Expectation Maximization, Gaussian Mixture Model, Image Clustering.
screenshots. Let’s talk about how it removes all disadvantages of k mean: Better Initialization strategy: Since we are using K mean++ initialization strategy so it is very less likely that we will end up getting wrong cluster formations. Varying cluster density: Unlike k mean it has varying cluster