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\(SC^2\): A Selection-Based Consensus Clustering Approach

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Progress in Advanced Computing and Intelligent Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 564))

Abstract

Consensus clustering, also called clustering ensemble, is a method of improving quality and robustness in clustering by optimally combining an ensemble of clusterings generated in different ways. In this work, we introduce our approach that is based on a selection-based model and use cumulative voting strategy in order to arrive at a consensus . We demonstrate the performance of our proposed method on several benchmark datasets and show empirically that it outperforms some well-known consensus clustering algorithms.

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Authors and Affiliations

  1. College of Engineering and Management, Kolaghat, WB, India

    Arko Banerjee

  2. C.V. Raman College of Engineering, Bhubaneswar, Odisha, India

    Bibhudendu Pati & Chhabi Rani Panigrahi

Authors
  1. Arko Banerjee
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  2. Bibhudendu Pati
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  3. Chhabi Rani Panigrahi
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Corresponding author

Correspondence to Arko Banerjee .

Editor information

Editors and Affiliations

  1. Faculty of Computer Science, Bialystok University of Technology, Białystok, Poland

    Khalid Saeed

  2. Dept. of Computer Science & Engg., University of Calcutta Dept. of Computer Science & Engg., Kolkata, West Bengal, India

    Nabendu Chaki

  3. C. V. Raman College of Engineering, Bhubaneswar, Odisha, India

    Bibudhendu Pati

  4. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Sambit Bakshi

  5. Department of Computer Science and Engineering, National Institute of Technology, Rourkela, Rourkela, Odisha, India

    Durga Prasad Mohapatra

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Cite this paper

Banerjee, A., Pati, B., Panigrahi, C.R. (2018). \(SC^2\): A Selection-Based Consensus Clustering Approach. In: Saeed, K., Chaki, N., Pati, B., Bakshi, S., Mohapatra, D. (eds) Progress in Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 564. Springer, Singapore. https://doi.org/10.1007/978-981-10-6875-1_18

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  • DOI: https://doi.org/10.1007/978-981-10-6875-1_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6874-4

  • Online ISBN: 978-981-10-6875-1

  • eBook Packages: EngineeringEngineering (R0)

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