An Extensional Clustering Algorithm of FCM Based on Intuitionistic Extension Index

Qing Feng Liu

doi:10.4028/www.scientific.net/AMR.490-495.1372

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 490-495An Extensional Clustering Algorithm of FCM Based...

An Extensional Clustering Algorithm of FCM Based on Intuitionistic Extension Index

Abstract:

The fuzzy C-means algorithm is an iterative algorithm in which the desired number of clusters C and the initial clustering seeds has to be pre-defined. The seeds are modified in each stage of the algorithm and for each object a degree of membership to each of the clusters is estimated. In this paper, an extensional clustering algorithm of FCM based on an intuitionistic extension index, denoted E-FCM algorithm, is proposed. For comparing the performance of the above mentioned two algorithms, the experimental results of three benchmark data sets show that the E-FCM algorithm outperforms the FCM algorithm.

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Periodical:

Advanced Materials Research (Volumes 490-495)

Pages:

1372-1376

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.490-495.1372

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Online since:

March 2012

Authors:

Qing Feng Liu

Keywords:

E-FCM Algorithm, Fuzzy C-Means (FCM), Intuitionistic Fuzzy Membership

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