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Online Clustering Based Concept Lattice Reduction

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Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016) (SoCPaR 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 614))

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Abstract

We proposed concept lattice reduction using evolving clustering method. Since evolving clustering method is an online learning approach, it is to be proved quite a time saving for concept lattice reduction. Furthermore, evolving clustering method yielded better concept lattice reduction than state-of-the-art. To demonstrate the effectiveness of the proposed approach, we experimented with two health care datasets namely tuberculosis and hypertension datasets.

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Author information

Authors and Affiliations

  1. Center of Excellence in Analytics, Institute for Development and Research in Banking Technology, Castle Hills Road no. 1, Masab Tank, Hyderabad, 500057, India

    Kumar Ravi & Vadlamani Ravi

  2. School of Computer and Information Sciences, University of Hyderabad, Hyderabad, 500046, India

    Kumar Ravi

Authors
  1. Kumar Ravi
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  2. Vadlamani Ravi
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Corresponding author

Correspondence to Vadlamani Ravi .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research, Machine Intelligence Research Labs (MIR Labs), Auburn, Washington, USA

    Ajith Abraham

  2. VIT University, Vellore, Tamil Nadu, India

    Aswani Kumar Cherukuri

  3. School of Engineering, Polytechnic of Porto (ISEP/IPP), Porto, Portugal

    Ana Maria Madureira

  4. Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Ravi, K., Ravi, V. (2018). Online Clustering Based Concept Lattice Reduction. In: Abraham, A., Cherukuri, A., Madureira, A., Muda, A. (eds) Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016). SoCPaR 2016. Advances in Intelligent Systems and Computing, vol 614. Springer, Cham. https://doi.org/10.1007/978-3-319-60618-7_68

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  • DOI: https://doi.org/10.1007/978-3-319-60618-7_68

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60617-0

  • Online ISBN: 978-3-319-60618-7

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