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

Chun Wei Tsai, Chu Sing Yang, Ming Chao Chiang

研究成果: Conference contribution

17 引文 斯高帕斯(Scopus)

摘要

In this paper, we present an efficient algorithm, called Pattern Reduction (PR) algorithm, to reduce the time required for data clustering based on iterative clustering algorithms. Conceptually similar to a lossy data compression scheme, this algorithm removes at each iteration those data patterns that are close to the centroid of a cluster or remain in the same cluster for a certain number of iterations in a row and are thus unlikely to be moved again from one cluster to another at later iterations by computing a new pattern to represent all the data patterns removed. Our simulation results - from 2 to 1,000 dimensions and 150 to 6,000,000 patterns - indicate that the proposed algorithm can reduce the computation time of k-means, Generic k-means Algorithm (GKA) and k-means with Genetic Algorithm (KGA) from 10% up to about 80% and that for high dimensional data sets, it can even reduce the computation time for more than 70%.

原文English
主出版物標題2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
頁面504-509
頁數6
DOIs
出版狀態Published - 2007 十二月 1
事件2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 - Montreal, QC, Canada
持續時間: 2007 十月 72007 十月 10

出版系列

名字Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN(列印)1062-922X

Other

Other2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
國家/地區Canada
城市Montreal, QC
期間07-10-0707-10-10

All Science Journal Classification (ASJC) codes

  • 工程 (全部)

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