Fuzzy c-Means Clustering with Mutual Relation Constraints
Recently, semi-supervised clustering attracts many researchers’ interest. In particular, constraint-based semi-supervised clustering is focused and the constraints of must-link and cannot-link play very important role in the clustering. There are many kinds of relations as well as must-link or cannot-link and one of the most typical relations is the trade-off relation. Thus, in this paper we formulate the trade-off relation and propose a new “semi-supervised” concept called mutual relation. Moreover, we construct two types of new clustering algorithms with the mutual relation constraints based on the well-known and useful fuzzy c-means, called fuzzy c-means with the mutual relation constraints.
KeywordsUnlabeled Data Typical Relation Uncertain Data Mutual Relation Tolerance Vector
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