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Using Genetic Algorithm to Create an Ensemble Machine Learning Models to Predict Tennis

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Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1 (FTC 2022 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 559))

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Abstract

In this paper, we illustrate our study of using genetic algorithms and machine learning to create an ensemble technique, which is used to predict tennis games using limited amounts of data. The genetic algorithm was used to improve the game representations, derived from the players’ statistics differences, to be utilized by the machine learning algorithms. The use of genetic algorithms also reduced the dependence on human expertise in creating the game representations. The majority of the ensemble models we generated were either as good or performed higher than the predictions based on just the player’ official rankings.

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Author information

Authors and Affiliations

  1. Abilene Christian University, Abilene, TX, USA

    Arisoa S. Randrianasolo

  2. South Dakota School of Mines and Technology, Rapid City, SD, USA

    Larry D. Pyeatt

Authors
  1. Arisoa S. Randrianasolo
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  2. Larry D. Pyeatt
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Corresponding author

Correspondence to Arisoa S. Randrianasolo .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Randrianasolo, A.S., Pyeatt, L.D. (2023). Using Genetic Algorithm to Create an Ensemble Machine Learning Models to Predict Tennis. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 1. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-031-18461-1_45

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