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Shapley Values in Classification Problems with Triadic Formal Concept Analysis

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Conceptual Knowledge Structures (CONCEPTS 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14914))

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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.

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Notes

  1. 1.

    The workshops on Interpretable Machine Learning: https://sites.google.com/view/ whi2018 and https://sites.google.com/view/hill2019.

  2. 2.

    One more important requirement is that any hypothesis should be supported by no less than two examples to ensure generalization. However, following [14], we omit this constraint.

  3. 3.

    Rounding is up to three significant figures.

  4. 4.

    https://github.com/EgurnovD/TriclusteringToolbox.

  5. 5.

    https://github.com/dimachine/TriShap/.

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Acknowledgements

We would like to thank Dmitry Egurnov and Roman Nabatchikov for their help with Triclustering Toolbox experimentation. The work of the last author is an output of a research project implemented as part of the Basic Research Program at HSE University. This research was also supported in part through computational resources of HPC facilities at HSE University.

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Authors and Affiliations

  1. La Rochelle Université, La Rochelle, France

    Martin Waffo Kemgne

  2. University of Dschang, Dschang, Cameroon

    Blaise Bleriot Koguep Njionou

  3. Bern University of Applied Sciences, Bern, Switzerland

    Leonard Kwuida

  4. HSE University, Moscow, Russia

    Dmitry I. Ignatov

Authors
  1. Martin Waffo Kemgne
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  2. Blaise Bleriot Koguep Njionou
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  3. Leonard Kwuida
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  4. Dmitry I. Ignatov
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Corresponding author

Correspondence to Dmitry I. Ignatov .

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Editors and Affiliations

  1. University of Málaga, Málaga, Spain

    Inma P. Cabrera

  2. IRISA, Rennes, France

    Sébastien Ferré

  3. TU Dresden, Dresden, Germany

    Sergei Obiedkov

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Kemgne, M.W., Njionou, B.B.K., Kwuida, L., Ignatov, D.I. (2024). Shapley Values in Classification Problems with Triadic Formal Concept Analysis. In: Cabrera, I.P., Ferré, S., Obiedkov, S. (eds) Conceptual Knowledge Structures. CONCEPTS 2024. Lecture Notes in Computer Science(), vol 14914. Springer, Cham. https://doi.org/10.1007/978-3-031-67868-4_6

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