Paper Info
Title
Minimum-Size Bases of Association Rules
Abstract
We focus on confidence-bounded association rules; we model a rather practical situation in which the confidence threshold is fixed by the user, as usually happens in applications. Within this model, we study notions of redundancy among association rules from a fundamental perspective: we discuss several existing alternative definitions and provide new characterizations and relationships between them. We show that these alternatives correspond actually to just two variants, which differ in the special treatment of full-confidence implications. For each of these two notions of redundancy, we show how to construct complete bases of absolutely minimum size.
Year
DOI
Venue
2008
10.1007/978-3-540-87479-9_24
ECML/PKDD (1)
Keywords
Field
DocType
practical situation,association rules,new characterization,confidence threshold,minimum-size bases,minimum size,fundamental perspective,full-confidence implication,confidence-bounded association rule,association rule,complete base,existing alternative definition
Theoretical computer science,Redundancy (engineering),Association rule learning,Artificial intelligence,Mathematics,Machine learning
Conference
Volume
ISSN
Citations 
5211
0302-9743
6
PageRank 
References 
Authors
0.51
22
1
Name
Order
Citations
PageRank
José L. Balcázar170162.06