Volume 15 Number 3 (May. 2020)
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JSW 2020 Vol.15(3): 74-85 ISSN: 1796-217X
doi: 10.17706/jsw.15.3.74-85

Clustering Center Optimization under-Sampling Method for Unbalanced Data

Haitao Li, Mingjie Zhuang*
 College of Engineering, Huaqiao University , Quanzhou, 362021, Fujian, China

Abstract—When the number of data in one class is significantly larger or less than the data in other class, under learning algorithm for classification, a problem of learning generalization occurs to the specific class and this is called imbalanced data problem. In this paper, a method of under-sampling based on the optimization cluster center selection (BCUSM)is proposed. First of all, the cluster center selection of K-means clustering algorithm is optimized, the initial cluster center is obtained by calculation, instead of random selection. The optimized method is called OICSK-means.....

Index Terms— Clustering, unbalanced data, under-sampling,classification.

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Cite: Haitao Li, Mingjie Zhuang, "Clustering Center Optimization under-Sampling Method for Unbalanced Data," Journal of Software vol. 15, no. 3, pp. 74-85, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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