Paper Info
Title
Interpretability analysis of fuzzy association rules supported by fingrams.
Abstract
This work extends fuzzy inference-grams (fingrams) to fuzzy association rules (FAR), yielding FAR-Fingrams. Their analysis pays attention to interpretability issues. An important open problem in association rule mining is the huge number of frequent itemsets and interesting rules to uncover and communicate to the user. FAR-Fingrams address such problem through visual analysis. They ease the selection of rules according to the user's preferences and quality criteria. A new metric to construct fingrams is proposed, reflecting the particularities of FAR. Finally, some of the potentials of FAR-Fingrams are overviewed over a real-world problem that deals with user-preferences.
Year
Venue
Keywords
2013
PROCEEDINGS OF THE 8TH CONFERENCE OF THE EUROPEAN SOCIETY FOR FUZZY LOGIC AND TECHNOLOGY (EUSFLAT-13)
Interpretability,fuzzy association rules,rule co-firing,social network analysis
Field
DocType
Volume
Interpretability,Open problem,Fuzzy logic,Association rule learning,Artificial intelligence,Fuzzy association rules,Machine learning,Mathematics
Conference
32.0
ISSN
Citations 
PageRank 
1951-6851
4
0.42
References 
Authors
16
4
Name
Order
Citations
PageRank
David P. Pancho1414.95
José M. Alonso2609.86
J. Alcalá-Fdez3205974.03
Luis Magdalena4108660.49