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title:
 
Improved Fuzzy Art Method for Initializing K-means
publication:
 
IJCIS
volume-issue:   3 - 3
pages:   274 - 279
ISSN:
  1875-6883
DOI:
  doi:10.2991/ijcis.2010.3.3.3 (how to use a DOI)
author(s):
 
Sevinc Ilhan, Nevcihan Duru, Esref Adali
publication date:
 
September 2010
keywords:
 
Clustering, K-means clustering, initial center determination, Improved Fuzzy ART method.
abstract:
 
The K-means algorithm is quite sensitive to the cluster centers selected initially and can perform different clusterings depending on these initialization conditions. Within the scope of this study, a new method based on the Fuzzy ART algorithm which is called Improved Fuzzy ART (IFART) is used in the determination of initial cluster centers. By using IFART, better quality clusters are achieved than Fuzzy ART do and also IFART is as good as Fuzzy ART about capable of fast clustering and capability on large scaled data clustering. Consequently, it is observed that, with the proposed method, the clustering operation is completed in fewer steps, that it is performed in a more stable manner by fixing the initialization points and that it is completed with a smaller error margin compared with the conventional K-means.
copyright:
 
© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
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