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Review of Metaheuristic Techniques for Feature Selection

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Soft Computing: Theories and Applications

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 627))

Abstract

Due to the rise of high-dimensional datasets in various sectors, feature selection is one of the most important issues. The primary goal of the feature selection problem is to lower the dimension of the feature set while retaining the performance accuracy. Several techniques of feature selection have been developed to obtain the optimal subset of features. To obtain optimal features, metaheuristics are modern optimization techniques that are used by the research community. In this paper, four groups of metaheuristic techniques have been identified based on their behavior. The classifier name, datasets, and assessment metrics for the metaheuristic methods used to solve the feature selection challenges are provided. After reviewing the papers, difficulties and problems are also observed while trying to use various metaheuristic methods to find the best subset of features. For those researchers who desire to continue their work on creating or refining metaheuristic techniques for feature selection, several research gaps are also mentioned.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Manipal University Jaipur, Jaipur, India

    Sanat Jain & Ashish Jain

  2. Department of Computer Science and Engineering, Manipal University Jaipur, Jaipur, India

    Mahesh Jangid

Authors
  1. Sanat Jain
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  2. Ashish Jain
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  3. Mahesh Jangid
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Corresponding author

Correspondence to Ashish Jain .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, India

    Rajesh Kumar

  2. Western Norway University of Applied Sciences, Bergen, Norway

    Ajit Kumar Verma

  3. Department of Computer Science, Shobhit University, Gangoh, India

    Tarun K. Sharma

  4. Department of Instrumentation and Control Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India

    Om Prakash Verma

  5. University Institute of Technology, Himachal Pradesh University, Shimla, Himachal Pradesh, India

    Sanjay Sharma

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Jain, S., Jain, A., Jangid, M. (2023). Review of Metaheuristic Techniques for Feature Selection. In: Kumar, R., Verma, A.K., Sharma, T.K., Verma, O.P., Sharma, S. (eds) Soft Computing: Theories and Applications. Lecture Notes in Networks and Systems, vol 627. Springer, Singapore. https://doi.org/10.1007/978-981-19-9858-4_33

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