Extracting Decision Rules from Qualitative Data via Sugeno Utility Functionals - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2018

Extracting Decision Rules from Qualitative Data via Sugeno Utility Functionals

Abstract

Sugeno integrals are qualitative aggregation functions. They are used in multiple criteria decision making and decision under uncertainty, for computing global evaluations of items, based on local evaluations. The combination of a Sugeno integral with unary order preserving functions on each criterion is called a Sugeno utility functionals (SUF). A noteworthy property of SUF is that they represent multi-threshold decision rules, while Sugeno integrals represent single-threshold ones. However, not all sets of multi-threshold rules can be represented by a single SUF. In this paper, we consider functions defined as the minimum or the maximum of several SUF. These max-SUF and min-SUF can represent all functions that can be described by a set of multi-threshold rules, i.e., all order-preserving functions on finite scales. We study their potential advantages as a compact representation of a big set of rules, as well as an intermediary step for extracting rules from empirical datasets.
Fichier principal
Vignette du fichier
ipmu-hal-version-1.pdf (310.82 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01670924 , version 1 (21-12-2017)

Identifiers

  • HAL Id : hal-01670924 , version 1

Cite

Quentin Brabant, Miguel Couceiro, Didier Dubois, Henri Prade, Agnès Rico. Extracting Decision Rules from Qualitative Data via Sugeno Utility Functionals. International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018), Jun 2018, Cadiz, France. pp.253-265. ⟨hal-01670924⟩
368 View
197 Download

Share

Gmail Facebook X LinkedIn More