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Modified Soft Rough set for Multiclass Classification

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Computational Intelligence, Cyber Security and Computational Models

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 246))

Abstract

Rough set theory has been applied to several domains because of its ability to handle imperfect knowledge. Most recent extension of rough set is soft rough set, where parameterized subsets of a universal set are basic building blocks for lower and upper approximations of a subset. In this paper, a new model of soft rough set, which is called modified soft rough set (MSR) where information granules are finer than soft rough sets, is applied for classification of medical data. In this paper, rough-set-based quick reduct approach is applied for selecting relevant features and MSR is applied for multiclass classification problem and the proposed work is compared with bijective soft set (BSS)-based classification, naïve Bayes, and decision table classifier algorithms based on evaluation metrics.

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Authors and Affiliations

  1. Department of Computer Science, Periyar University, Salem, 636011, India

    S. Senthilkumar, H. Hannah Inbarani & S. Udhayakumar

Authors
  1. S. Senthilkumar
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  2. H. Hannah Inbarani
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  3. S. Udhayakumar
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Corresponding author

Correspondence to S. Senthilkumar .

Editor information

Editors and Affiliations

  1. Applied Mathematics and Computational Sciences, PSG College of Technology, Coimbatore, Tamil Nadu, India

    G. Sai Sundara Krishnan

  2. Applied Mathematics and Computational Sciences, PSG College of Technology, Coimbatore, Tamil Nadu, India

    R. Anitha

  3. Applied Mathematics and Computational Sciences, PSG College of Technology, Coimbatore, Tamil Nadu, India

    R. S. Lekshmi

  4. Applied Mathematics and Computational Sciences, PSG College of Technology, Coimbatore, Tamil Nadu, India

    M. Senthil Kumar

  5. Department of Mathematics, Ryerson University, Toronto, Ontario, Canada

    Anthony Bonato

  6. University of Basque Country, Paseo Manuel De Lardizalbal 1, San Sebastian, Spain

    Manuel Graña

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© 2014 Springer India

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Senthilkumar, S., Inbarani, H.H., Udhayakumar, S. (2014). Modified Soft Rough set for Multiclass Classification. In: Krishnan, G., Anitha, R., Lekshmi, R., Kumar, M., Bonato, A., Graña, M. (eds) Computational Intelligence, Cyber Security and Computational Models. Advances in Intelligent Systems and Computing, vol 246. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1680-3_41

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  • DOI: https://doi.org/10.1007/978-81-322-1680-3_41

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1679-7

  • Online ISBN: 978-81-322-1680-3

  • eBook Packages: EngineeringEngineering (R0)

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