Shapley Values in Classification Problems with Triadic Formal Concept Analysis

Kemgne, Martin Waffo; Njionou, Blaise Bleriot Koguep; Kwuida, Léonard; Ignatov, Dmitry I. (2024). Shapley Values in Classification Problems with Triadic Formal Concept Analysis In: Cabrera, Inma P.; Ferré, Sébastien; Obiedkov, Sergei (eds.) Conceptual Knowledge Structures: First International Joint Conference, CONCEPTS 2024, Cádiz, Spain, September 9–13, 2024, Proceedings. Lecture Notes in Computer Science: Vol. 14914 (pp. 83-96). Cham: Springer Nature 10.1007/978-3-031-67868-4_6

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The JSM-method is a supervised classification method, used in machine learning. The JSM-method has recently been used in Triadic Concept Analysis to classify objects. In this paper, we show how Shapley value of a cooperative game with transferable utilities, can be used to give the importance or individual contribution of each attribute-condition pair of a particular object, for its classification to a particular class.

Item Type:	Book Section (Book Chapter)
Division/Institute:	Business School > Institute for Applied Data Science & Finance Business School > Institute for Applied Data Science & Finance > Applied Data Science Business School
Name:	Kemgne, Martin Waffo; Njionou, Blaise Bleriot Koguep; Kwuida, Léonard0000-0002-9811-0747; Ignatov, Dmitry I.; Cabrera, Inma P.; Ferré, Sébastien and Obiedkov, Sergei
ISSN:	1611-3349
ISBN:	978-3-031-67867-7
Series:	Lecture Notes in Computer Science
Publisher:	Springer Nature
Language:	English
Submitter:	Léonard Kwuida
Date Deposited:	21 Aug 2024 10:44
Last Modified:	21 Aug 2024 10:44
Publisher DOI:	10.1007/978-3-031-67868-4_6
URI:	https://arbor.bfh.ch/id/eprint/22209