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arXiv · 1602.07277

A Simple Approach to Sparse Clustering

Ery Arias-Castro·Xiao Pu
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Abstract

Consider the problem of sparse clustering, where it is assumed that only a subset of the features are useful for clustering purposes. In the framework of the COSA method of Friedman and Meulman, subsequently improved in the form of the Sparse K-means method of Witten and Tibshirani, a natural and simpler hill-climbing approach is introduced. The new method is shown to be competitive with these two methods and others.

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Ery Arias-Castro, Xiao Pu. 2016-09-11. A Simple Approach to Sparse Clustering. https://doi.org/10.1016/j.csda.2016.08.003

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