On K-means algorithm with the use of Mahalanobis distances
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Date
2014-01-01
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Journal ISSN
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Publisher
Statistics & Probability Letters
Abstract
Abstract The K-means algorithm is commonly used with the Euclidean metric. While the use of Mahalanobis distances seems to be a straightforward extension of the algorithm, the initial estimation of covariance matrices can be complicated. We propose a novel approach for initializing covariance matrices.
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Keywords
K-means algorithm, Mahalanobis distance, Initialization
Citation
Igor Melnykov, Volodymyr Melnykov, On K-means algorithm with the use of Mahalanobis distances, In Statistics & Probability Letters, Volume 84, 2014, Pages 88-95