Evaluation and optimization of frequent, closed and maximal association rule based classification.

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Evaluation and optimization of frequent, closed and maximal association rule based classification.

Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand. The algorithms for closed and maximal itemsets mining significantly reduce the volume of rules discovered and c...

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Bibliographic Details
Main Authors:	Shaharanee, I., Hadzic, Fedja
Format:	Journal Article
Published:	Springer Science+Business Media BV 2014
Subjects:	Rule optimization Interestingness measures Statistical analysis
Online Access:	http://hdl.handle.net/20.500.11937/34009

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