Anca Ralescu
Adv. Artif. Intell. Mach. Learn., 1 (1):86-93
1. Anca Ralescu: University of Cincinnati, Cincinnati, OH 45219, USA.
DOI: 10.54364/AAIML.2021.1106
Article History: Received on: 10-Jun-21, Accepted on: 25-Jun-21, Published on: 02-Jul-21
Corresponding Author: Anca Ralescu
Email: ralescal@ucmail.uc.edu
Citation: Javier Viaña, Stephan Ralescu, Kelly Cohen, Vladik Kreinovich and Anca Ralescu (2021). Why Cauchy Membership Functions: Efficiency. Adv. Artif. Intell. Mach. Learn., 1 (1 ):86-93
Fuzzy techniques depend heavily on eliciting meaningful membership functions for the fuzzy sets used. Often such functions
are obtained from data. Just as often they are obtained from experts knowledgeable of the domain and the problem being
addressed. However, there are cases when neither is possible, for example because of insufficient data, or unavailable experts.
What functions should we choose and what should guide such choice? This paper argues in favor of using Cauchy membership
functions, thus named because their expression is similar to that of the Cauchy distributions. The paper provides a theoretical
explanation for this choice.