Summary

International Symposium on Nonlinear Theory and its Applications

2009

Session Number:C1L-B

Session:

Number:C1L-B4

Two types of Tolerant Hard c-Means Clustering

HAMASUNA Yukihiro,  ENDO Yasunori,  

pp.-

Publication Date:2009/10/18

Online ISSN:2188-5079

DOI:10.34385/proc.43.C1L-B4

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Summary:
In this paper, we will propose two types of tolerant hard c-means clustering (THCM). One is an alternating optimization form and the other is a sequential algorithm. Introducing a concept of clusterwise tolerance, we have proposed tolerant fuzzy c-means clustering from the viewpoint of handling data more flexibly. In the concept of clusterwise tolerance, a constraint for tolerance vector which restricts the upper bound of tolerance vector is used. First, the concept of clusterwise tolerance is introduced into hard c-means clustering. Second, optimization problem for tolerant hard c-means clustering is formulated. Third, new clustering algorithms are constructed based on the explicit optimal solutions. Finally, effectiveness of proposed algorithms is verified through numerical examples.