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
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.