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A Rule Induction Model Empowered by Fuzzy-Rough Particle Swarm Optimization Algorithm for Classification of Microarray Dataset

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Computational Intelligence in Data Mining - Volume 3

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 33))

Abstract

Selection of small number of genes from thousands of genes which may be responsible for causing cancer is still a challenging problem. Various computational intelligence methods have been used to deal with this issue. This study introduces a novel hybrid technique based on Fuzzy-Rough Particle Swarm Optimization (FRPSO) to identify a minimal subset of genes from thousands of candidate genes. Efficiency of the proposed method is tested with a rule based classifier MODLEM using three benchmark gene expression cancer datasets. This study reveals that the hybrid evolutionary Fuzzy-Rough induction rule model can identify the hidden relationship between the genes responsible for causing the disease. It also provides a rule set for diagnosis and prognosis of cancer datasets which helps to design drugs for the disease. Finally the function of identified genes are analyzed and validated from gene ontology website, DAVID, which shows the relationship of genes with the disease.

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Authors and Affiliations

  1. North Orissa University, Baripada, Odisha, India

    Sujata Dash

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  1. Sujata Dash
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Correspondence to Sujata Dash .

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Editors and Affiliations

  1. School of Electrical and Information Engineering, University of South Australia, South Australia, Australia

    Lakhmi C. Jain

  2. Computer Science and Engineering, Veer Surendra Sai University of Technolo, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Eng., National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Dash, S. (2015). A Rule Induction Model Empowered by Fuzzy-Rough Particle Swarm Optimization Algorithm for Classification of Microarray Dataset. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 3. Smart Innovation, Systems and Technologies, vol 33. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2202-6_26

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  • DOI: https://doi.org/10.1007/978-81-322-2202-6_26

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2201-9

  • Online ISBN: 978-81-322-2202-6

  • eBook Packages: EngineeringEngineering (R0)

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