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Consensus Algorithm for Bi-clustering Analysis

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Computational Science – ICCS 2022 (ICCS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13351))

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Abstract

Bi-clustering is an unsupervised data mining technique, which involves concurrent clustering of rows and columns of a two-dimensional data matrix. It has been demonstrated that bi-clustering may allow accurate and comprehensive mining of information, important for many practical applications. Numerous algorithms for data bi-clustering were proposed in the literature, based on different approaches and leading, in general, to different outputs. In this paper we propose a consensus method for combining outputs of many bi-clustering algorithms for improved quality of predictions. The proposed algorithm includes two steps. The first step, “assignment”, leads to detecting groups of bi-clusters of high similarity and the second step, “trimming”, results in transforming a group of similar bi-clusters into one bi-cluster of high quality. We demonstrate, on the basis of both simulated and real datasets, that using our algorithm highly improves quality of bi-clustering. We also provide an easy to use software tool, which includes implementations of several bi-clustering algorithms and our consensus method.

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Acknowledgements

This work was funded by Polish National Science Centre, OPUS grant 2016/21/B /ST6/02153 (AP,WL); research project (RAU-6, 2020) and projects for young scientists of the Silesian University of Technology (Gliwice, Poland) (PF,MS).

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Authors and Affiliations

  1. Department of Computer Graphics, Vision and Digital Systems, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 2A, 44 -100, Gliwice, Poland

    Paweł Foszner, Wojciech Labaj, Andrzej Polanski & Michal Staniszewski

Authors
  1. Paweł Foszner
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  2. Wojciech Labaj
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  3. Andrzej Polanski
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  4. Michal Staniszewski
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Corresponding author

Correspondence to Paweł Foszner .

Editor information

Editors and Affiliations

  1. Brunel University London, London, UK

    Derek Groen

  2. University of Amsterdam, Amsterdam, The Netherlands

    Clélia de Mulatier

  3. AGH University of Science and Technology, Krakow, Poland

    Maciej Paszynski

  4. University of Amsterdam, Amsterdam, The Netherlands

    Valeria V. Krzhizhanovskaya

  5. University of Tennessee at Knoxville, Knoxville, TN, USA

    Jack J. Dongarra

  6. University of Amsterdam, Amsterdam, The Netherlands

    Peter M. A. Sloot

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Foszner, P., Labaj, W., Polanski, A., Staniszewski, M. (2022). Consensus Algorithm for Bi-clustering Analysis. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13351. Springer, Cham. https://doi.org/10.1007/978-3-031-08754-7_61

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  • DOI: https://doi.org/10.1007/978-3-031-08754-7_61

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