How Many Clusters Are There? - An Essay on the Basic Notions of Clustering.
Bernd ReuschPublished in: KES (1) (2008)
Keyphrases
- clustering algorithm
- hierarchical clustering
- overlapping clusters
- cluster analysis
- data clustering
- clustering method
- fuzzy clustering
- document clustering
- k means
- clustering approaches
- clustering scheme
- data points
- self organizing maps
- agglomerative hierarchical clustering
- model based clustering
- clustering framework
- incremental clustering
- unsupervised clustering
- graph clustering
- subspace clustering
- kohonen self organizing maps
- hierarchical clustering algorithm
- cluster centers
- cluster validation
- density based clustering
- cluster membership
- inter cluster
- density based clustering algorithm
- clustering quality
- homogeneous groups
- clustering result
- arbitrary shape
- soft clustering
- hierarchical agglomerative clustering
- clustering analysis
- agglomerative clustering
- data objects
- clustering procedure
- intra cluster
- cluster validity
- unsupervised learning
- fuzzy k means
- disjoint clusters
- clusters of arbitrary shapes
- classical clustering algorithms
- similar objects
- validity measures
- dimensionality reduction
- similarity matrix
- fuzzy c means
- cluster structure
- spatial clustering
- constrained clustering
- high dimensional datasets
- meaningful clusters
- arbitrary shaped
- document clusters
- fuzzy clustering algorithm
- validity index
- validity indices
- high dimension space
- pairwise