Finding compact and well-separated clusters: Clustering using silhouette coefficients.
Adil M. BagirovRamiz M. AliguliyevNargiz SultanovaPublished in: Pattern Recognit. (2023)
Keyphrases
- clustering algorithm
- hierarchical clustering
- overlapping clusters
- cluster analysis
- clustering scheme
- data clustering
- k means
- clustering method
- clustering framework
- clustering approaches
- graph clustering
- document clustering
- incremental clustering
- unsupervised clustering
- fuzzy clustering
- cluster centers
- agglomerative hierarchical clustering
- clustering quality
- subspace clustering
- density based clustering
- disjoint clusters
- density based clustering algorithm
- hierarchical clustering algorithm
- clustering result
- constrained clustering
- model based clustering
- inter cluster
- data points
- validity measures
- meaningful clusters
- spatial clustering
- clustering ensemble
- intra cluster
- affinity propagation
- self organizing maps
- spectral clustering
- fuzzy c means
- soft clustering
- categorical data
- multi view
- classical clustering algorithms
- kohonen self organizing maps
- hierarchical agglomerative clustering
- unsupervised learning
- homogeneous groups
- clustering procedure
- linear combination
- high dimensional data
- similarity matrix
- clustering analysis
- synthetic datasets
- cluster structure
- normalized cut
- fuzzy clustering algorithm
- clusters of arbitrary shapes
- affinity measure
- validity index
- arbitrary shape
- dissimilarity matrix
- cluster membership
- data objects
- cluster validation
- subspace clusters
- consensus clustering
- high dimensional datasets
- dense regions
- outlier detection
- similar objects
- cluster labels
- agglomerative clustering
- wavelet coefficients