Yeah, a Gaussian Mixture Model (GMM) is a very useful method which is closely related to k-means. It allows for other shapes than just spheres which tends to be

Yeah, a Gaussian Mixture Model (GMM) is a very useful method which is closely related to k-means. It allows for other shapes than just spheres which tends to be very useful in practice. In addition to the probabilistic cluster membership (as you mention). Not only is the same EM algorithm used to find GMM parameters, but initial cluster assignment is usually done with k-means (typically a variation dubbed k-means++)