On 11/05/2014 01:10 AM, Sturla Molden wrote: > "Pagliari, Roberto" <rpagli...@appcomsci.com> > wrote: > >> If that's the case, why is that the underlying implementation of k-means >> does not take this into account? > Because then it would be the "classification EM algorithm" (often called > CEM) instead of k-means. By definition, k-means is CEM constrained with > equal cluster size and equal and spherical covariance matrices. > If you want different sized clusters, you might want to look into GMMs, which learn a covariance structure. In KMeans, the cluster structure is always given by the voronoi cells of the means, which means that the border between the clusters is exactly in the middle of the two clusters centers.
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