JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2018, Vol. 48 ›› Issue (3): 140-145.doi: 10.6040/j.issn.1672-3961.0.2017.410

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Coefficient of variation clustering algorithm for non-uniform data

YANG Tianpeng1, XU Kunpeng1, CHEN Lifei1,2*   

  1. 1. College of Mathematics and Informatics, Fujian Normal University, Fuzhou 350117, Fujian, China;
    2. Digit Fujian Internet-of-Things Laboratory of Environmental Monitoring, Fujian Normal University, Fuzhou 350117, Fujian, China
  • Received:2017-08-24 Online:2018-06-20 Published:2017-08-24

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Abstract: Affected by the “uniform effect”, a problem existed in the partition-based algorithms remained on open and challenging taskdue to handling. To solve this problem, a clustering algorithm based on coefficient of variation was proposed. The “uniform effect” caused by K-means-type partitioning clustering algorithm from the view of clustering optimization was analyzed. Instead of the squared error, a new measure of dispersion for non-uniform data was proposed relied on the coefficient of variation. The clustering objective optimization function was defined using a new non-uniform data dissimilarity formula, which was proposed based on the coefficient of variation. According to the local optimization method, the clustering algorithm process was given. The experimental results on real and synthetic non-uniform datasets showed that the clustering accuracy of CVCN was better than K-means, Verify2, ESSC.

Key words: clustering, partition-based clustering, coefficient of variation, K-means, uniform effect, non-uniform data

CLC Number: 

  • TP311
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