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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.

## History

## Chapter number

9## Pagination

262-272## ISBN-13

9780444518149## ISBN-10

0444518142## Edition

1st ed.## Language

eng## Publication classification

B1.1 Book chapter, B Book chapter## Copyright notice

2005, Elsevier## Extent

16## Editor/Contributor(s)

Klement E, Mesiar R## Publisher

Elsevier## Place of publication

Boston, Mass.## Title of book

Logical, algebraic, analytic, and probabilistic aspects of triangular norms## Usage metrics

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