Volume 3, Issue 3, September 2010, Pages 274 - 279
Improved Fuzzy Art Method for Initializing K-means
- Sevinc Ilhan, Nevcihan Duru, Esref Adali
- Corresponding Author
- Sevinc Ilhan
Available Online 29 June 2010.
- https://doi.org/10.2991/ijcis.2010.3.3.3How to use a DOI?
- Clustering, K-means clustering, initial center determination, Improved Fuzzy ART method.
- 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.
- 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 -