Machine Learning, Clustering, Python, Gaussian Mixture Model, Unsupervised Learning.
values: full: Each mixture component has its general covariance matrix. tied: All mixture components share the same general covariance matrix. diag: Each mixture component has its diagonal covariance matrix. spherical: Each mixture component has its single variance value, resulting in spherical