Paper Info
Title
Multicriteria Attractiveness Evaluation of Decision and Association Rules
Abstract
The work is devoted to multicriteria approaches to rule evaluation. It analyses desirable properties (in particular the property M, property of confirmation and hypothesis symmetry) of popular interestingness measures of decision and association rules. Moreover, it analyses relationships between the considered interestingness measures and enclosure relationships between the sets of non-dominated rules in different evaluation spaces. It's main result is a proposition of a multicriteria evaluation space in which the set of non-dominated rules will contain all optimal rules with respect to any attractiveness measure with the property M. By determining the area of rules with desirable value of a confirmation measure in the proposed multicriteria evaluation space one can narrow down the set of induced rules only to the valuable ones. Furthermore, the work presents an extension of an apriori-like algorithm for generation of rules with respect to attractiveness measures possessing valuable properties and shows some applications of the results to analysis of rules induced from exemplary datasets.
Year
DOI
Venue
2009
10.1007/978-3-642-03281-3_8
T. Rough Sets
Keywords
Field
DocType
different evaluation space,confirmation measure,valuable property,association rules,attractiveness measure,multicriteria evaluation space,multicriteria attractiveness evaluation,non-dominated rule,desirable property,property m,proposed multicriteria evaluation space,property m.,association rule
Data mining,Proposition,Computer science,Gain function,Association rule learning,Attractiveness
Journal
Volume
ISSN
Citations 
10
0302-9743
11
PageRank 
References 
Authors
0.67
38
1
Name
Order
Citations
PageRank
Izabela Szczęch1567.90