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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38095

Title: A Fuzzy K-means Clustering Algorithm Using Cluster Center Displacement
Authors: CHIH-TANG CHANG
JIM Z. C. LAI
MU-DER JENG
Contributors: 國立臺灣海洋大學:電機工程學系
Keywords: pattern recognition
vector quantization
fuzzy k-means clustering
data clustering
knowledge discovery
Date: 2011
Issue Date: 2016-08-03T02:47:26Z
Publisher: JOURNAL OF INFORMATION SCIENCE AND ENGINEERING
Abstract: Abstract:In this paper, we present a fuzzy k-means clustering algorithm using the cluster center
displacement between successive iterative processes to reduce the computational
complexity of conventional fuzzy k-means clustering algorithm. The proposed method,
referred to as CDFKM, first classifies cluster centers into active and stable groups. Our
method skips the distance calculations for stable clusters in the iterative process. To
speed up the convergence of CDFKM, we also present an algorithm to determine the initial
cluster centers for CDFKM. Compared to the conventional fuzzy k-means clustering
algorithm, our proposed method can reduce computing time by a factor of 3.2 to 6.5 using
the data sets generated from the Gauss Markov sequence. Our algorithm can reduce
the number of distance calculations of conventional fuzzy k-means clustering algorithm
by 38.9% to 86.5% using the same data sets.
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/38095
Appears in Collections:[電機工程學系] 期刊論文

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