Visual Sampling Based Clustering Approach VSC

Guo Wei; Wang Shi-tong; Chen Ke; Han Bin

Volume 28 Issue 4

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Guo Wei, Wang Shi-tong, Chen Ke, Han Bin. Visual Sampling Based Clustering Approach VSC[J]. Journal of Electronics & Information Technology, 2006, 28(4): 597-602.

Citation:

Guo Wei, Wang Shi-tong, Chen Ke, Han Bin. Visual Sampling Based Clustering Approach VSC[J]. Journal of Electronics & Information Technology, 2006, 28(4): 597-602.

Guo Wei, Wang Shi-tong, Chen Ke, Han Bin. Visual Sampling Based Clustering Approach VSC[J]. Journal of Electronics & Information Technology, 2006, 28(4): 597-602.

Citation:

Guo Wei, Wang Shi-tong, Chen Ke, Han Bin. Visual Sampling Based Clustering Approach VSC[J]. Journal of Electronics & Information Technology, 2006, 28(4): 597-602.

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Visual Sampling Based Clustering Approach VSC

Received Date: 2004-07-08
Rev Recd Date: 2004-11-25
Publish Date: 2006-04-19

Abstract

Abstract

Based on the visual sampling principle, the generalized visual sampling based clustering approach VSC is proposed. The clustering approach incorporates the visual sampling principle with the famous Weber law such that it has two distinctive advantages: firstly, it is insensitive to initial conditions; secondly, the reasonable clustering number can be effectively determined by the new Weber-law-based clustering validity index. The experimental results demonstrate its success. Moreover, the link relationship between our approach and algorithm SCA (Similarity-based Clustering Algorithm) recently proposed by Yang Miin-Shen, et al. (2004) is derived. Both theoretic analyses and experimental results show that in many cases, the approach here has almost the same clustering results as algorithm SCA. This fact reveals that the approach can be used to overcome the drawback of SCA, i.e., the parameter is very difficult to be well determined.

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References(1)

References

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