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Cluster Ensembles Optimization Using Coral Reefs Optimization Algorithm

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Artificial Neural Networks and Machine Learning – ICANN 2016 (ICANN 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9887))

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Abstract

The main aim of this paper is to combine multiple partitions generated by different clustering algorithms into a single clustering solution (consensus partition), using a new bio-inspired optimization technique to optimize the cluster ensembles. In this proposed technique, the cluster ensembles are heterogeneously created and the initial partitions are combined through a method which uses the Coral Reefs Optimization algorithm, resulting in a consensus partition.

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Author information

Authors and Affiliations

  1. Department of Informatics and Applied Mathematics, Federal University of Rio Grande do Norte, Natal, RN, Brazil

    Huliane M. Silva, Anne M. P. Canuto & João C. Xavier-Júnior

  2. Digital Metropolis Institute, Federal University of Rio Grande do Norte, Natal, RN, Brazil

    Anne M. P. Canuto, Inácio G. Medeiros & João C. Xavier-Júnior

Authors
  1. Huliane M. Silva
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  2. Anne M. P. Canuto
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  3. Inácio G. Medeiros
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  4. João C. Xavier-Júnior
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Corresponding author

Correspondence to Anne M. P. Canuto .

Editor information

Editors and Affiliations

  1. University of Lausanne, Lausanne, Switzerland

    Alessandro E.P. Villa

  2. University of Lausanne, Lausanne, Switzerland

    Paolo Masulli

  3. Universitat Politécnica de Catalunya, Terrrassa, Spain

    Antonio Javier Pons Rivero

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© 2016 Springer International Publishing Switzerland

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Silva, H.M., Canuto, A.M.P., Medeiros, I.G., Xavier-Júnior, J.C. (2016). Cluster Ensembles Optimization Using Coral Reefs Optimization Algorithm. In: Villa, A., Masulli, P., Pons Rivero, A. (eds) Artificial Neural Networks and Machine Learning – ICANN 2016. ICANN 2016. Lecture Notes in Computer Science(), vol 9887. Springer, Cham. https://doi.org/10.1007/978-3-319-44781-0_33

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  • DOI: https://doi.org/10.1007/978-3-319-44781-0_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44780-3

  • Online ISBN: 978-3-319-44781-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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