Mahalanobis metrics for k-means algorithms
 
 
 

Summary
Solutions obtained for a k-means algorithm depends heavily on the starting partition. In this article an aid is developed for implementing initialization methods particularly suited when all the cluster covariances matrices are presumed to be identical.
 

keywords
covariance estimates, determinant minimization, multiple quickselect
 

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