Improved Inter-Cluster Separation Algorithm

Abstract:

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The inter-cluster separation (ICS) algorithm adds the separation item into the objective function to minimize the fuzzy Euclidean distance and maximize the inter-cluster separation. However, ICS is sensitive to noisy data, so an improved inter-cluster separation (IICS) algorithm is proposed to deal with this problem. It is claimed that IICS is an incorporation of ICS and improved possibilistic c-means (IPCM) clustering. IICS can produce both possibilities and memberships simultaneously, and it overcomes the noise sensitivity problem of ICS and the coincident clusters problem of possibilistic c-means (PCM) clustering. Further, IICS does not depend on the parameters that exist in IPCM. The experimental results show that IICS compares favorably with ICS.

Info:

Periodical:

Key Engineering Materials (Volumes 439-440)

Edited by:

Yanwen Wu

Pages:

361-366

DOI:

10.4028/www.scientific.net/KEM.439-440.361

Citation:

X. H. Wu et al., "Improved Inter-Cluster Separation Algorithm", Key Engineering Materials, Vols. 439-440, pp. 361-366, 2010

Online since:

June 2010

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Price:

$35.00

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