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Mixtures of multivariate normals can be regarded as a method of fuzzy clustering, where each point has a probability of coming from each of the component Gauss
by Bostonian 5y ago
Mixtures of multivariate normals can be regarded as a method of fuzzy clustering,
where each point has a probability of coming from each of the component Gaussians. The EM (expectation maximization) algorithm can be used to fit mixture models.
- jononor 5y agoYeah, 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++)