Computer Science ›› 2018, Vol. 45 ›› Issue (1): 62-66.doi: 10.11896/j.issn.1002-137X.2018.01.009

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Three-way Clustering Analysis Based on Dynamic Neighborhood

WANG Ping-xin, LIU Qiang, YANG Xi-bei and MI Ju-sheng   

  • Online:2018-01-15 Published:2018-11-13

Abstract: Most of the existing clustering methods are two-way clustering,which are based on the assumption that a cluster must be represented by a set with crisp boundary.However,assigning uncertain points into a cluster will reduce the accuracy of the method.Three-way clustering is an overlapping clustering which describes each cluster by core region and fringe region.This paper presented a strategy for converting a two-way cluster to three-way cluster using the neighborhood of the samples.In the proposed method,a two-way cluster is shrunk according to whether the neighborhood of sample are contained in this cluster and it is stretched according to whether the neighborhood of sample intersects with this cluster.The shrunk result is called core region and the difference between the shrunk result and stretched result is regarded as the fringe region.Experiment using the proposed method on UCI data sets shows that this strategy is effective in improving the structure and F1 values of clustering results.

Key words: Three-way clustering,Neighborhood,K-means clustering,Spectral clustering

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