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D-MBPSO: An Unsupervised Feature Selection Algorithm Based on PSO

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Innovations in Bio-Inspired Computing and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 424))

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Abstract

High dimensional data with limited number of samples is a challenging task in microarray data classification. Unsupervised gene selection methods handle such data of existing methods. Various methods are available to handle the data with class labels whereas some data are mislabeled and unreliable. We propose an unsupervised filter based method known as dynamic MBPSO (D-MBPSO) which integrates MBPSO into filter approach by defining new fitness function and it is independent of any learning model. The main aim of the filter approach is to quantify the relevance based on the intrinsic properties of the data. The proposed method is applied on benchmark microarray datasets and the results are compared with well known unsupervised gene selection methods using different classifiers. The proposed method has a remarkable ability to obtain reduced feature subset with good classification accuracy.

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Authors and Affiliations

  1. Department of Information Technology, PSG College of Technology, Coimbatore, India

    K. Umamaheswari

  2. Department of Information Technology, SRM University, Chennai, India

    M. Dhivya

Authors
  1. K. Umamaheswari
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  2. M. Dhivya
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Corresponding authors

Correspondence to K. Umamaheswari or M. Dhivya .

Editor information

Editors and Affiliations

  1. Dep. of Computer Science, VŠB – Technical Univ. of Ostrava, Ostrava, Czech Republic

    Václav Snášel

  2. (MIR Labs), Scientific Net Innov & Res Excel, Auburn, Washington, USA

    Ajit Abraham

  3. Faculty of Elec. Eng. & Comp. Sci., VÅ B - Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Pavel Krömer

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  5. Fac of Info & Comm, Comp Inte & Tech Lab, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Umamaheswari, K., Dhivya, M. (2016). D-MBPSO: An Unsupervised Feature Selection Algorithm Based on PSO. In: Snášel, V., Abraham, A., Krömer, P., Pant, M., Muda, A. (eds) Innovations in Bio-Inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-28031-8_31

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  • DOI: https://doi.org/10.1007/978-3-319-28031-8_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28030-1

  • Online ISBN: 978-3-319-28031-8

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