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Fitting triangular norms to empirical data
This chapter discusses some specific tools that can be used to build triangular norms based on a finite number of (possibly noisy) observations. Such problem arises in applications, when observed data (e.g., decision patterns of experts) need to be modelled with a special class of functions, such as triangular norms. We show how this problem can be transformed into a constrained regression problem, and then efficiently solved. We also discuss related operators: uninorms, nullnorms and associative copulas.
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Title of book
Logical, algebraic, analytic, and probabilistic aspects of triangular normsChapter number
9Pagination
262 - 272Publisher
ElsevierPlace of publication
Boston, Mass.ISBN-13
9780444518149ISBN-10
0444518142Edition
1st ed.Language
engPublication classification
B1.1 Book chapter; B Book chapterCopyright notice
2005, ElsevierExtent
16Editor/Contributor(s)
E Klement, R MesiarUsage metrics
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