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Improved Slime Mould Algorithm based on Firefly Algorithm for feature selection: A case study on QSAR model

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Abstract

Feature selection (FS) methods are necessary to develop intelligent analysis tools that require data preprocessing and enhancing the performance of the machine learning algorithms. FS aims to maximize the classification accuracy by minimizing the number of selected features. This paper presents a new FS method using a modified Slime mould algorithm (SMA) based on the firefly algorithm (FA). In the developed SMAFA, FA is adopted to improve the exploration of SMA, since it has high ability to discover the feasible regions which have optima solution. This will lead to enhance the convergence by increasing the quality of the final output. SMAFA is evaluated using twenty UCI datasets and also with comprehensive comparisons to a number of the existing MH algorithms. To further assess the applicability of SMAFA, two high-dimensional datasets related to the QSAR modeling are used. Experimental results verified the promising performance of SMAFA using different performance measures.

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Acknowledgements

This project was supported financially by the Academy of Scientific Research and Technology (ASRT), Egypt, Grant 6619).

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Authors and Affiliations

  1. Department of Computer, Damietta University, Damietta, 34517, Egypt

    Ahmed A. Ewees

  2. Faculty of Computer Sciences and Informatics, Amman Arab University, 11953, Amman, Jordan

    Laith Abualigah

  3. Department of Electrical Engineering, Faculty of Engineering, Fayoum University, Fayoum, Egypt

    Dalia Yousri

  4. Department of Statistics and Informatics, University of Mosul, Mosul, Iraq

    Zakariya Yahya Algamal

  5. State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, 430079, China

    Mohammed A. A. Al-qaness

  6. Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, 44519, Egypt

    Rehab Ali Ibrahim & Mohamed Abd Elaziz

  7. Faculty of Computer Science, Nahda University, Beni Suef, 62521, Egypt

    Mohamed Abd Elaziz

  8. Academy of Scientific Research and Technology (ASRT), Cairo, Egypt

    Mohamed Abd Elaziz

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  1. Ahmed A. Ewees
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  2. Laith Abualigah
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  4. Zakariya Yahya Algamal
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  5. Mohammed A. A. Al-qaness
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  7. Mohamed Abd Elaziz
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Correspondence to Mohammed A. A. Al-qaness.

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Ewees, A.A., Abualigah, L., Yousri, D. et al. Improved Slime Mould Algorithm based on Firefly Algorithm for feature selection: A case study on QSAR model. Engineering with Computers 38 (Suppl 3), 2407–2421 (2022). https://doi.org/10.1007/s00366-021-01342-6

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