A time-efficient pattern reduction algorithm for k-means clustering

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Title:	A time-efficient pattern reduction algorithm for k-means clustering
Authors:	Chiang, Ming-Chao Tsai, Chun-Wei Yang, Chu-Sing
Contributors:	應用空間資訊系
Keywords:	Data clustering k-means Pattern reduction
Date:	2011-02
Issue Date:	2013-10-14 14:57:44 (UTC+8)
Publisher:	Elsevier
Abstract:	This paper presents an efficient algorithm, called pattern reduction (PR), for reducing the computation time of k-means and k-means-based clustering algorithms. The proposed algorithm works by compressing and removing at each iteration patterns that are unlikely to change their membership thereafter. Not only is the proposed algorithm simple and easy to implement, but it can also be applied to many other iterative clustering algorithms such as kernel-based and population-based clustering algorithms. Our experiments—from 2 to 1000 dimensions and 150 to 10,000,000 patterns—indicate that with a small loss of quality, the proposed algorithm can significantly reduce the computation time of all state-of-the-art clustering algorithms evaluated in this paper, especially for large and high-dimensional data sets.
Relation:	Information Sciences , 181(4), pp.716-731
Appears in Collections:	[Dept. of Applied Geoinformatics] Periodical Articles

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