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Feature Selection Based on a Decision Tree Genetic Algorithm

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Hybrid Artificial Intelligent Systems (HAIS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14001))

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Abstract

The feature selection problem has become a key undertaking within machine learning. For classification problems, it is known to reduce the computational complexity of parameter estimation, but also it adds an important contribution to the explainability aspects of the results. In this paper, a genetic algorithm for feature selection is proposed. The importance, as well as the effectiveness of features selected by each individual, is evaluated by using decision trees. The feature importance indicated by the decision tree is used during selection and recombination. The tree inducted by the best individual in the population is used for classification. Numerical experiments illustrate the behavior of the approach.

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Notes

  1. 1.

    version 1.1.1.

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Acknowledgements

This work was supported by a grant of the Ministry of Research, Innovation and Digitization, CNCS - UEFISCDI, project number PN-III-P1-1.1-TE-2021-1374, within PNCDI III.

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Authors and Affiliations

  1. Centre for the Study of Complexity, Babeş-Bolyai University, Cluj-Napoca, Romania

    Mihai-Alexandru Suciu & Rodica Ioana Lung

Authors
  1. Mihai-Alexandru Suciu
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  2. Rodica Ioana Lung
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Corresponding author

Correspondence to Mihai-Alexandru Suciu .

Editor information

Editors and Affiliations

  1. University of Deusto, Bilbao, Spain

    Pablo García Bringas

  2. University of Leon, León, Spain

    Hilde Pérez García

  3. University of La Rioja, Logroño, La Rioja, Spain

    Francisco Javier Martínez de Pisón

  4. Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  5. Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  6. University of Burgos, Burgos, Spain

    Álvaro Herrero

  7. University of A Coruña, Ferrol - Coruña, Spain

    José Luis Calvo Rolle

  8. University of A Coruña, Ferrol - Coruña, Spain

    Héctor Quintián

  9. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Suciu, MA., Lung, R.I. (2023). Feature Selection Based on a Decision Tree Genetic Algorithm. In: García Bringas, P., et al. Hybrid Artificial Intelligent Systems. HAIS 2023. Lecture Notes in Computer Science(), vol 14001. Springer, Cham. https://doi.org/10.1007/978-3-031-40725-3_37

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  • DOI: https://doi.org/10.1007/978-3-031-40725-3_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-40724-6

  • Online ISBN: 978-3-031-40725-3

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