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How to build aggregation operators from data
Author(s) -
Beliakov G.
Publication year - 2003
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.10120
Subject(s) - associative property , commutative property , data aggregator , range (aeronautics) , computer science , regression , mathematics , theoretical computer science , data mining , pure mathematics , statistics , computer network , materials science , wireless sensor network , composite material
This article discusses a range of regression techniques specifically tailored to building aggregation operators from empirical data. These techniques identify optimal parameters of aggregation operators from various classes (triangular norms, uninorms, copulas, ordered weighted aggregation (OWA), generalized means, and compensatory and general aggregation operators), while allowing one to preserve specific properties such as commutativity or associativity. © 2003 Wiley Periodicals, Inc.