JOURNAL ARTICLE
Mining fuzzy quantitative association rules
Abstract
Given a relational database and a set of fuzzy terms defined for some attributes we consider the problem of mining fuzzy quantitative association rules that may contain crisp values, intervals, and fuzzy terms in both antecedent and consequent. We present an algorithm extended from the equi-depth partition (EDP) algorithm for solving this problem. Our approach combines interval partition with pre-defined fuzzy terms and is more general.
Keywords:
Association rule learning Partition (number theory) Fuzzy set Antecedent (behavioral psychology) Data mining Fuzzy logic Fuzzy set operations Computer science Fuzzy classification Defuzzification Fuzzy number Type-2 fuzzy sets and systems Mathematics Artificial intelligence Combinatorics
Metrics
73
Cited By
23.04
FWCI (Field Weighted Citation Impact)
13
Refs
0.99
Citation Normalized Percentile
Is in top 1%
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Citation History
Topics
Data Mining Algorithms and Applications
Physical Sciences → Computer Science → Information Systems
Rough Sets and Fuzzy Logic
Physical Sciences → Computer Science → Computational Theory and Mathematics
Data Management and Algorithms
Physical Sciences → Computer Science → Signal Processing
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