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A Refined Rough k-Means Clustering with Hybrid Threshold

  • Conference paper
Rough Sets and Current Trends in Computing (RSCTC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7413))

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Abstract

In this paper, we propose a new type of adaptive weight based on the definiteness of rough clusters and a hybrid threshold by combining the difference and distance threshold. And then, we refine the algorithm for assigning objects based on the hybrid thresholds to ensure that the outliers in inline positions and rectangle positions to be represented reasonably. At last, some experiments are provided to compare this refined RCM with the original RCM.

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chendu, 610051, P.R. China

    Hailiang Wang & Mingtian Zhou

Authors
  1. Hailiang Wang
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  2. Mingtian Zhou
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, S4S 0A2, Regina, SK, Canada

    JingTao Yao

  2. School of Information Science and Technology, Southwest Jiaotong University, 610031, Chengdu, P.R. China

    Yan Yang

  3. Institute of Computing Science, Poznan University of Technology, Piotrowo 2, 60-965, Poznan, Poland

    Roman Słowiński

  4. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco

  5. School of Management and Engineering, Nanjing University, 210093, Nanjing, Jiangsu, P.R. China

    Huaxiong Li

  6. Machine Intelligence Unit, Indian Statistical Institute (ISI), 700108, Kolkata, India

    Sushmita Mitra

  7. Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008, Warsaw, Poland

    Lech Polkowski

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© 2012 Springer-Verlag Berlin Heidelberg

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Wang, H., Zhou, M. (2012). A Refined Rough k-Means Clustering with Hybrid Threshold. In: Yao, J., et al. Rough Sets and Current Trends in Computing. RSCTC 2012. Lecture Notes in Computer Science(), vol 7413. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32115-3_3

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  • DOI: https://doi.org/10.1007/978-3-642-32115-3_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32114-6

  • Online ISBN: 978-3-642-32115-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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