A novel K-means and K-medoids algorithms for clustering non-spherical-shape clusters non-sensitive to outliers.
Jaafar HeidariNegin DaneshpourAli ZangenehPublished in: Pattern Recognit. (2024)
Keyphrases
- k means
- clustering algorithm
- data clustering
- arbitrary shape
- agglomerative hierarchical clustering
- hierarchical clustering
- clustering approaches
- cluster analysis
- clustering quality
- data points
- classical clustering algorithms
- clustering method
- unsupervised clustering
- cluster centers
- spectral clustering
- self organizing maps
- clustering framework
- bisecting k means
- document clustering
- text clustering
- center based clustering
- validity indices
- fuzzy clustering algorithm
- hierarchical clustering algorithms
- subspace clustering
- hierarchical clustering algorithm
- star shaped
- overlapping clusters
- fuzzy k means
- graph clustering
- rough k means
- validity measures
- clustering result
- constrained clustering
- hierarchical agglomerative clustering
- fuzzy c means
- model based clustering
- density based clustering
- dense regions
- synthetic datasets
- kernel based clustering
- fuzzy clustering
- shape model
- graph partitioning