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Clustering Based on Classification Quality (CCQ)

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Recent Advances on Soft Computing and Data Mining (SCDM 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 549))

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Abstract

Clustering a set of objects into homogeneous classes is a fundamental operation in data mining. Categorical data clustering based on rough set theory has been an active research area in the field of machine learning. However, pure rough set theory is not well suited for analyzing noisy information systems. In this paper, an alternative technique for categorical data clustering using Variable Precision Rough Set model is proposed. It is based on the classification quality of Variable Precision Rough theory. The technique is implemented in MATLAB. Experimental results on three benchmark UCI datasets indicate that the technique can be successfully used to analyze grouped categorical data because it produces better clustering results.

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Author information

Authors and Affiliations

  1. Department of Information System, Ahmad Dahlan University, Yogyakarta, Indonesia

    Iwan Tri Riyadi Yanto

  2. Department of Industrial Engineering, Telkom University, Bandung, West Java, Indonesia

    Rd Rohmat Saedudin

  3. Department of Information System, Tunas Bangsa AMIK and STIKOM, Pematangsiantar, Indonesia

    Dedy Hartama

  4. Department of Information System, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

Authors
  1. Iwan Tri Riyadi Yanto
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  2. Rd Rohmat Saedudin
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  3. Dedy Hartama
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  4. Tutut Herawan
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Corresponding author

Correspondence to Iwan Tri Riyadi Yanto .

Editor information

Editors and Affiliations

  1. Department of Information System, University of Malaya, Kuala Lumpur, Malaysia

    Tutut Herawan

  2. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Rozaida Ghazali

  3. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Nazri Mohd Nawi

  4. Universiti Tun Hussein Onn Malaysia, Batu Pahat, Malaysia

    Mustafa Mat Deris

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Yanto, I.T.R., Saedudin, R.R., Hartama, D., Herawan, T. (2017). Clustering Based on Classification Quality (CCQ). In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2016. Advances in Intelligent Systems and Computing, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-319-51281-5_33

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  • DOI: https://doi.org/10.1007/978-3-319-51281-5_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51279-2

  • Online ISBN: 978-3-319-51281-5

  • eBook Packages: EngineeringEngineering (R0)

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