A New Index Based on Sparsity Measures for Comparing Fuzzy Partitions

被引：0
|
作者：
Quere, Romain [1 ]
Frelicot, Carl [1 ]
机构：
[1] Univ Rochelle, La Rochelle, France
来源：
STRUCTURAL, SYNTACTIC, AND STATISTICAL PATTERN RECOGNITION | 2012年 / 7626卷
关键词：
Cluster analysis; Rand index; Jaccard Index; Transfert distance; Sparsity measure; Fuzzy residual implications;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
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.
引用
收藏
页码：291 / 300
页数：10
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