I am new to using GMMs. I was not able to find any appropriate help online. Could anyone please provide me right resource on "How to decide if using GMM fits to my problem?" or in case of classification problems "How to decide if I have to use SVM classification or GMM classification?"
In my opinion, you can perform GMM when you know that the data points are mixtures of a gaussian distribution. Basically forming clusters with different mean and standard deviation. There's a nice diagram on scikit-learn website. L
An approach is to find the clusters using soft clustering methods and then see if they are gaussian. If they are then you can apply a GMM model which represents the whole dataset.
GMMs are usually a good place to start if your goal is to either (1) cluster observations, (2) specify a generative model, or (3) estimate densities. In fact, for clustering, GMMs are a superset of k-means.