International Journal of Computational Intelligence Systems

Volume 3, Issue 3, September 2010, Pages 274 - 279

Improved Fuzzy Art Method for Initializing K-means

Authors
Sevinc Ilhan, Nevcihan Duru, Esref Adali
Corresponding Author
Sevinc Ilhan
Available Online 29 June 2010.
DOI
https://doi.org/10.2991/ijcis.2010.3.3.3How to use a DOI?
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.
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This is an open access article distributed under the CC BY-NC license.

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
3 - 3
Pages
274 - 279
Publication Date
2010/06
ISSN
1875-6883
DOI
https://doi.org/10.2991/ijcis.2010.3.3.3How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - JOUR
AU  - Sevinc Ilhan
AU  - Nevcihan Duru
AU  - Esref Adali
PY  - 2010
DA  - 2010/06
TI  - Improved Fuzzy Art Method for Initializing K-means
JO  - International Journal of Computational Intelligence Systems
SP  - 274
EP  - 279
VL  - 3
IS  - 3
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.2010.3.3.3
DO  - https://doi.org/10.2991/ijcis.2010.3.3.3
ID  - Ilhan2010
ER  -