Repository logo
  • English
  • Deutsch
  • Français
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. CRIS
  3. Publication
  4. Shapley Values in Classification Problems with Triadic Formal Concept Analysis
 

Shapley Values in Classification Problems with Triadic Formal Concept Analysis

URI
https://arbor.bfh.ch/handle/arbor/37129
Version
Published
Date Issued
2024
Author(s)
Kemgne, Martin Waffo
Njionou, Blaise Bleriot Koguep
Kwuida, Léonard  
Ignatov, Dmitry I.
Editor(s)
Cabrera, Inma P.
Ferré, Sébastien
Obiedkov, Sergei
Type
Book Chapter
Language
English
Abstract
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.
ISBN
978-3-031-67867-7
Publisher DOI
10.1007/978-3-031-67868-4_6
Series/Report No.
Lecture Notes in Computer Science
ISSN
1611-3349
Publisher URL
https://link.springer.com/chapter/10.1007/978-3-031-67868-4_6
Organization
Institut Applied Data Science & Finance  
Applied Data Science  
Wirtschaft  
Volume
14914
Publisher
Springer Nature
Submitter
Kwuida, Léonard
Citation apa
Kemgne, M. W., Njionou, B. B. K., Kwuida, L., & Ignatov, D. I. (2024). Shapley Values in Classification Problems with Triadic Formal Concept Analysis (I. P. Cabrera, S. Ferré, & S. Obiedkov, Eds.; Vol. 14914). Springer Nature. https://arbor.bfh.ch/handle/arbor/37129
About ARBOR

Built with DSpace-CRIS software - System hosted and mantained by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback
  • Our institution