A New Index Based On Sparsity Measures For Comparing Fuzzy Partitions
STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION(2012)
摘要
This article adresses the problem of assessing how close two strict and/or fuzzy partitions are. A new index based on a measurement of the sparsity of the contingency matrix crossing the partitions is proposed that satisfies the required properties formulated within the paper and presents a low complexity. It is compared to well-known existing indices of the literature, such as the Rand and the Jaccard indices, the transfert distance and some of their recent fuzzy counterparts.
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关键词
Cluster analysis,Rand index,Jaccard Index,Transfert distance,Sparsity measure,Fuzzy residual implications
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