I'm learning the GMM clustering algorithm. I don't understand how it can used as a classifier. Here are my thought:
1) GMM is an unsupervised ML algorithm. At least that's how
sklearn categorizes it.
2) Unsupervised methods can cluster data, but can't make predictions.
However, sklearn's user guide clearly applid GMM as a classifier to the iris dataset.
If I have to guess, maybe after clustering, each cluster is assigned to a class label based on some kind of majority voting. However, I can't find any documentation. Could someone shed more light on this process from unsupervised to supervised learning?
A related question: when using GMM as a classifier, is it common practice to simply make
n_components=n_classes, instead of checking AIC, BIC, etc.?