An Expansion of X-Means for Automatically Determining the Optimal Number of Clusters a^EUR" Progressive Iterations of K-Means and Merging of the Clusters.
Tsunenori IshiokaPublished in: Computational Intelligence (2005)
Keyphrases
- cluster centers
- clustering algorithm
- k means
- hierarchical clustering
- cluster validity
- data clustering
- cluster analysis
- initial set
- data points
- unsupervised clustering
- self organizing maps
- hierarchical clustering algorithm
- determine the optimal number
- fuzzy clustering
- agglomerative clustering
- constrained clustering
- fuzzy clustering algorithm
- hierarchical agglomerative clustering
- agglomerative hierarchical clustering
- clustering approaches
- fuzzy k means
- clustering method
- small number
- computational complexity
- homogeneous groups
- kohonen self organizing maps
- cluster centroids
- graph clustering
- data objects
- document clustering
- input data
- dynamic programming