A hybrid multi-objective feature selection method based on Shapley value and binary state transition algorithm

Ming Li; Renyou Xie; Jituo Tian

doi:10.1117/12.2685933

28 July 2023 A hybrid multi-objective feature selection method based on Shapley value and binary state transition algorithm

Ming Li, Renyou Xie, Jituo Tian

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Proceedings Volume 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023); 127560Q (2023) https://doi.org/10.1117/12.2685933
Event: 2023 3rd International Conference on Applied Mathematics, Modelling and Intelligent Computing (CAMMIC 2023), 2023, Tangshan, China

Abstract

Feature selection is a critical step in machine learning to reduce data dimensionality, whereas the conflicting objectives: minimizing the selected feature number, and minimizing the error rate of classification make it quite challenging. However, most existing feature selection algorithms only focus on one single objective. To address this issue, a hybrid multi-objective feature selection (MOFS) method based on Shapley value and binary state transition algorithm is proposed in this paper, named MOFS-BSTA. Additionally, to enhance the converge capability of MOFS-BSTA, a mutation operator is developed to produce more efficient candidate solutions, and a two-dimensional sorting strategy is designed to replace the fast non-dominated sorting strategy. Finally, MOFS-BSTA is tested on nine UCI datasets, and the results demonstrate that the MOFS-BSTA can obtain the better Pareto optimal solution set with less running time than conventional MOFS methods.

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Ming Li, Renyou Xie, and Jituo Tian "A hybrid multi-objective feature selection method based on Shapley value and binary state transition algorithm", Proc. SPIE 12756, 3rd International Conference on Applied Mathematics, Modelling, and Intelligent Computing (CAMMIC 2023), 127560Q (28 July 2023); https://doi.org/10.1117/12.2685933

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KEYWORDS

Feature selection

Micro optical fluidics

Binary data

Machine learning

Mathematical optimization

Education and training

Feature extraction

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