College of Engineering, Huaqiao University , Quanzhou, 362021, Fujian, China

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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.

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