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Interestingness Measures for Fuzzy Association Rules
[chapter]
2001
Lecture Notes in Computer Science
Data mining tries to discover interesting and surprising patterns among a given data set. An important task is to develop effective measures of interestingness for evaluating and ranking the discovered patterns. A good measure should give a high rank to patterns, which have strong evidence among data, but which yet are not too obvious. Thereby the initial set of patterns can be pruned before human inspection. In this paper we study interestingness measures for generalized quantitative
doi:10.1007/3-540-44794-6_13
fatcat:ixwnublh5nfajni4anc4zabdri