Clustering with Confidence: Finding Clusters with Statistical Guarantees.
Andreas HeneliusKai PuolamäkiHenrik BoströmPanagiotis PapapetrouPublished in: CoRR (2016)
Keyphrases
- clustering algorithm
- hierarchical clustering
- overlapping clusters
- cluster analysis
- k means
- data clustering
- clustering method
- self organizing maps
- fuzzy clustering
- unsupervised clustering
- clustering scheme
- incremental clustering
- density based clustering
- inter cluster
- hierarchical clustering algorithm
- clustering approaches
- intra cluster
- disjoint clusters
- agglomerative hierarchical clustering
- graph clustering
- document clustering
- clustering framework
- data points
- fuzzy c means
- density based clustering algorithm
- cluster centers
- classical clustering algorithms
- affinity propagation
- model based clustering
- clustering result
- cluster structure
- fuzzy clustering algorithm
- cluster validation
- fuzzy k means
- validity measures
- clustering quality
- arbitrary shape
- spatial clustering
- agglomerative clustering
- kohonen self organizing maps
- soft clustering
- cluster validity
- clustering procedure
- information theoretic
- statistical analysis
- meaningful clusters
- confidence intervals
- homogeneous groups
- validity index
- similarity matrix
- search results clustering
- clusters of arbitrary shapes
- data objects
- hierarchical agglomerative clustering
- high dimensional datasets
- similar objects
- affinity measure
- cluster validity index
- normalized cut
- spectral clustering