Dimensionality Reduction for k-means Clustering

07/26/2020

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by   Neophytos Charalambides, et al.

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35

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We present a study on how to effectively reduce the dimensions of the k-means clustering problem, so that provably accurate approximations are obtained. Four algorithms are presented, two feature selection and two feature extraction based algorithms, all of which are randomized.