RT Journal Article
T1 On the influence of dependent features in classification problems: A game-theoretic perspective
A1 Davila Pena, Laura
A1 Casas Méndez, Balbina
A1 Saavedra Nieves, Alejandro
K1 Classification problems
K1 Influence measure of features
K1 Dependent features
K1 Axiomatic characterization
K1 Banzhaf-Owen value
AB This paper deals with a new measure of the influence of each feature on the outcome in classification problems, accounting for potential dependencies among certain feature subsets. Within this framework, we consider a sample of individuals characterized by specific features, each feature encompassing a finite range of values, and classified based on a binary outcome. This measure turns out to be an influence measure explored in existing literature and related to cooperative game theory. We provide an axiomatic characterization of our proposed influence measure by tailoring properties from the cooperative game theory to our specific context. Furthermore, we demonstrate that our influence measure becomes a general characterization of the well-known Banzhaf-Owen value for games with a priori unions, from the perspective of classification problems. The definitions and results presented herein are illustrated through numerical examples and various applications, offering practical insights into our methodologies.
PB Elsevier
SN 1873-6793
YR 2025
FD 2025
LK https://hdl.handle.net/10347/44480
UL https://hdl.handle.net/10347/44480
LA eng
NO Expert Systems with Applications Volume 280, 25 June 2025, 127446
NO This work is part of the R+D+I project PID2021-124030NB-C32, granted by MICIU/AEI/10.13039/501100011033/, Spain and by “ERDF A way of making Europe”/EU. This research was also funded by Grupos de Referencia Competitiva ED431C 2021/24 from the Consellería de Cultura, Educación e Universidades, Xunta de Galicia, Spain
DS Minerva
RD 28 abr 2026