Clustering Center Optimization under-Sampling Method for Unbalanced Data

摘要

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.....