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BiETopti-BiClustering Ensemble Using Optimization Techniques

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Advances in Data Mining. Applications and Theoretical Aspects (ICDM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7987))

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Abstract

In this paper, we present an ensemble method for the biclustering problem that uses optimization techniques to generate consensus. Experiments have shown that the proposed method provides superior bi-clusters than the existing bi-clustering solutions most of the times. Bi-clustering problem has many applications including analysis of gene expression data.

This project is supported by University of Delhi.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Delhi, Delhi, 110007, India

    Geeta Aggarwal & Neelima Gupta

Authors
  1. Geeta Aggarwal
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  2. Neelima Gupta
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Editor information

Editors and Affiliations

  1. Institute of Computer Vision and Applied Computer Sciences, IBaI, Leipzig, Germany

    Petra Perner

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Aggarwal, G., Gupta, N. (2013). BiETopti-BiClustering Ensemble Using Optimization Techniques. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2013. Lecture Notes in Computer Science(), vol 7987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39736-3_14

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  • DOI: https://doi.org/10.1007/978-3-642-39736-3_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39735-6

  • Online ISBN: 978-3-642-39736-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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