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Gene Selection for Microarray Data Classification Using Hybrid Meta-Heuristics

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Modelling and Implementation of Complex Systems (MISC 2018)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 64))

Abstract

The hybridization of metaheuristics got a lot of interest lately. The crucial step lies in the choice of the hybrid methods. The major purpose is to make a tradeoff between exploitation and exploration concepts to create a more robust method. Hybrid metaheuristics are used as a solution to many optimization problems such as feature selection. In this paper we propose an hybridization between metaheuristics (PeSOA, FA, DE, AIS, BAT) for a best gene selection in microarray datasets. The main objective is to prove the efficiency of the proposed hybridization compared to the hybrid methods. The experimentations showed that PeSOA-C and HFA were competitive to their hybrid methods, on the other side, AIS-BAT was less promising compared to AIS. As results, we obtained a perfect 100% in case of Leukemia, Ovarian Cancer, Lymphoma and MLL-Leukemia datasets by the HFA hybridization with only 2%–4% of selected genes.

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Author information

Authors and Affiliations

  1. EEDIS Laboratory, Djillali Liabes University, Sidi Bel Abbes, Algeria

    Nassima Dif, Mohamed walid Attaoui & Zakaria Elberrichi

Authors
  1. Nassima Dif
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  2. Mohamed walid Attaoui
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  3. Zakaria Elberrichi
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Correspondence to Nassima Dif .

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Editors and Affiliations

  1. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Salim Chikhi

  2. Faculty of Technology, GeCoDe Laboratory, University of Saida, Saida, Algeria

    Abdelmalek Amine

  3. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Allaoua Chaoui

  4. Faculty of New Information and Communication Technologies, University of Constantine 2, Constantine, Algeria

    Djamel Eddine Saidouni

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Dif, N., Attaoui, M.w., Elberrichi, Z. (2019). Gene Selection for Microarray Data Classification Using Hybrid Meta-Heuristics. In: Chikhi, S., Amine, A., Chaoui, A., Saidouni, D.E. (eds) Modelling and Implementation of Complex Systems. MISC 2018. Lecture Notes in Networks and Systems, vol 64. Springer, Cham. https://doi.org/10.1007/978-3-030-05481-6_9

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