Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)

Why Kappa Regression?

Authors
Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Olga Kosheleva, Vladik Kreinovich
Corresponding Author
Julio C. Urenda
Available Online 30 August 2021.
DOI
https://doi.org/10.2991/asum.k.210827.063How to use a DOI?
Keywords
Kappa-regression distributions, Kappa-regression membership functions, Invariance
Abstract

A recent book provides examples that a new class of probability distributions and membership functions – called kappa-regression distributions and membership functions – leads, in many practical applications, to better data processing results than using previously known classes. In this paper, we provide a theoretical explanation for this empirical success – namely, we show that these distributions are the only ones that satisfy reasonable invariance requirements.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Cite this article

TY  - CONF
AU  - Julio C. Urenda
AU  - Orsolya Csiszár
AU  - Gábor Csiszár
AU  - József Dombi
AU  - György Eigner
AU  - Olga Kosheleva
AU  - Vladik Kreinovich
PY  - 2021
DA  - 2021/08/30
TI  - Why Kappa Regression?
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 478
EP  - 485
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.063
DO  - https://doi.org/10.2991/asum.k.210827.063
ID  - Urenda2021
ER  -