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Hybrid Fuzzy C-Means Using Bat Optimization and Maxi-Min Distance Classifier

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Advances in Computing and Data Sciences (ICACDS 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1046))

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Abstract

Fuzzy c-means (FCM) is a frequently used clustering method because of its efficiency, simplicity and easy implementation. Major drawbacks of FCM are sensitivity to initialization and local convergence problem. To overcome the drawbacks, the proposed method describes a hybrid FCM using Bat optimization and Maxi-min classifier. Maxi-min classifier is used to decide the count of clusters and then pass that count to randomized fuzzy c-means algorithm, which improves the performance. Bat optimization is a global optimization method used for solving many optimization problems due to its high convergence rate. Two popular datasets from kaggle are used to show the comparison between proposed technique and the fuzzy c means algorithm in terms of performance. Experiment results showing that the proposed technique is efficient and the results are encouraging.

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Authors and Affiliations

  1. Indian Institute of Technology (ISM), Dhanbad, India

    Rahul Kumar & Rajesh Dwivedi

  2. Vignan Foundation for Science Technology and Research, Vadlamudi, India

    Ebenezer Jangam

Authors
  1. Rahul Kumar
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  2. Rajesh Dwivedi
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  3. Ebenezer Jangam
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Corresponding author

Correspondence to Rajesh Dwivedi .

Editor information

Editors and Affiliations

  1. University of KwaZulu-Natal, Durban, South Africa

    Mayank Singh

  2. Computer Science and Engineering, Jaypee Institute of Information Technology, Waknaghat, Himachal Pradesh, India

    P.K. Gupta

  3. Department of Computer Science and Engineering, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

    Vipin Tyagi

  4. ÚTIA AV ČR, Institute of Information Theory and Automation, Prague 8, Praha, Czech Republic

    Jan Flusser

  5. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada

    Tuncer Ören

  6. CSE Department, Inderprastha Engineering College, Ghaziabad, Uttar Pradesh, India

    Rekha Kashyap

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Kumar, R., Dwivedi, R., Jangam, E. (2019). Hybrid Fuzzy C-Means Using Bat Optimization and Maxi-Min Distance Classifier. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T., Kashyap, R. (eds) Advances in Computing and Data Sciences. ICACDS 2019. Communications in Computer and Information Science, vol 1046. Springer, Singapore. https://doi.org/10.1007/978-981-13-9942-8_7

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  • DOI: https://doi.org/10.1007/978-981-13-9942-8_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9941-1

  • Online ISBN: 978-981-13-9942-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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