Why Kappa Regression?

Julio C. Urenda, Orsolya Csiszár, Gábor Csiszár, József Dombi, György Eigner, Olga Kosheleva, Vladik Kreinovich
2021 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for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)   unpublished
A recent book provides examples that a new class of probability distributions and membership functions -called kappa-regression distributions and membership functionsleads, 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.
doi:10.2991/asum.k.210827.063 fatcat:h2ujjpb2bjcmxewiski3we422a