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An Extension to Rough c-Means Clustering

  • Conference paper
Rough Sets and Knowledge Technology (RSKT 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6954))

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Abstract

The original form of the Rough c-means algorithm does not distinguish between data points in the boundary area. This paper presents an extended Rough c-means algorithm in which the distinction between data points in the boundary area is captured and used in the clustering procedure. Experimental results indicate that the proposed algorithm can yield more desirable clustering results in comparison to the original form of the Rough c-means algorithm.

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© 2011 Springer-Verlag Berlin Heidelberg

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Li, F., Liu, Q. (2011). An Extension to Rough c-Means Clustering. In: Yao, J., Ramanna, S., Wang, G., Suraj, Z. (eds) Rough Sets and Knowledge Technology. RSKT 2011. Lecture Notes in Computer Science(), vol 6954. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24425-4_29

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  • DOI: https://doi.org/10.1007/978-3-642-24425-4_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24424-7

  • Online ISBN: 978-3-642-24425-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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