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Modified Ant Colony Optimization Algorithm (MAnt-Miner) for Classification Rule Mining

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Intelligent Computing, Communication and Devices

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 308))

Abstract

Classification rule mining is an important task of data mining. Ant colony optimization (ACO) algorithms are applied successfully to various optimization problems. Earlier Ant-Miner, an ACO algorithm was used to discover the classification rules and predictive accuracy was determined. In this paper, modified ant colony optimization (MAnt-Miner) is proposed to generate the classification rules and to enhance the predictive accuracy. This method is applied on breast cancer data set, and the experimental result showed that the predictive accuracy of MAnt-Miner is better than Ant-Miner.

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Author information

Authors and Affiliations

  1. Siksha O Anusandhan University, Bhubaneswar, India

    Sarbeswara Hota & Alok Kumar Jagadev

  2. Department of IMCA, Utkal University, Bhubaneswar, India

    Pranati Satapathy

Authors
  1. Sarbeswara Hota
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  2. Pranati Satapathy
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  3. Alok Kumar Jagadev
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Corresponding author

Correspondence to Sarbeswara Hota .

Editor information

Editors and Affiliations

  1. University of Canberra, Faculty of Education, Science, Technology and Mathematics, Canberra, Australia, and University of South Australia, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  2. Department of Computer Science and Engin, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. Department of Premier and Cabinet, Office of the Chief Information Officer, Adelaide, South Australia, Australia

    Nikhil Ichalkaranje

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© 2015 Springer India

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Hota, S., Satapathy, P., Jagadev, A.K. (2015). Modified Ant Colony Optimization Algorithm (MAnt-Miner) for Classification Rule Mining. In: Jain, L., Patnaik, S., Ichalkaranje, N. (eds) Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 308. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2012-1_28

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  • DOI: https://doi.org/10.1007/978-81-322-2012-1_28

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2011-4

  • Online ISBN: 978-81-322-2012-1

  • eBook Packages: EngineeringEngineering (R0)

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