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A multi-objective feature selection method based on bacterial foraging optimization

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Abstract

Feature selection plays an important role in data preprocessing. The aim of feature selection is to recognize and remove redundant or irrelevant features. The key issue is to use as few features as possible to achieve the lowest classification error rate. This paper formulates feature selection as a multi-objective problem. In order to address feature selection problem, this paper uses the multi-objective bacterial foraging optimization algorithm to select the feature subsets and k-nearest neighbor algorithm as the evaluation algorithm. The wheel roulette mechanism is further introduced to remove duplicated features. Four information exchange mechanisms are integrated into the bacteria-inspired algorithm to avoid the individuals getting trapped into the local optima so as to achieve better results in solving high-dimensional feature selection problem. On six small datasets and ten high-dimensional datasets, comparative experiments with different conventional wrapper methods and several evolutionary algorithms demonstrate the superiority of the proposed bacteria-inspired based feature selection method.

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Acknowledgements

This work is partially supported by The National Natural Science Foundation of China (Grants Nos. 71571120, 71271140, 71471158, 71001072, and 61472257). Natural Science Foundation of Guangdong Province (2016A030310074, 2018A030310575), Shenzhen Science and Technology Plan (CXZZ20140418182638764), Research Foundation of Shenzhen University (85303/00000155), and Research Cultivation Project from Shenzhen Institute of Information Technology (ZY201717).

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Author notes

  1. Shuang Geng and Hong Wang contributed equally to this article.

Authors and Affiliations

  1. College of Management, Shenzhen University, Shenzhen, 518060, China

    Ben Niu, Wenjie Yi, Lijing Tan, Shuang Geng & Hong Wang

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  1. Ben Niu
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  2. Wenjie Yi
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  3. Lijing Tan
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  4. Shuang Geng
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  5. Hong Wang
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Correspondence to Shuang Geng or Hong Wang.

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Niu, B., Yi, W., Tan, L. et al. A multi-objective feature selection method based on bacterial foraging optimization. Nat Comput 20, 63–76 (2021). https://doi.org/10.1007/s11047-019-09754-6

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