Cluster-Volume-Based Merging Approach for Incrementally Evolving Fuzzy Gaussian Clustering - eGAUSS+.
Igor SkrjancPublished in: IEEE Trans. Fuzzy Syst. (2020)
Keyphrases
- clustering algorithm
- data clustering
- hierarchical clustering
- cluster analysis
- clustering framework
- overlapping clusters
- intra cluster
- clustering method
- clustering approaches
- k means
- unsupervised clustering
- inter cluster
- supervised clustering
- agglomerative clustering
- rough k means
- subspace clustering
- data points
- clustering procedure
- clustering scheme
- fuzzy clustering
- disjoint clusters
- clustering result
- constrained clustering
- validity measures
- cluster validation
- cluster membership
- cluster centers
- overlapping clustering
- clustering quality
- cluster structure
- agglomerative hierarchical clustering
- hierarchical clustering algorithm
- density based clustering
- homogeneous groups
- clustering analysis
- cluster validity
- document clustering
- density based clustering algorithm
- spectral clustering
- categorical data
- merging algorithm
- data objects
- instance level constraints
- rule based systems
- self organizing maps
- hierarchical agglomerative clustering
- semi supervised clustering
- pairwise
- unsupervised fuzzy clustering
- neighborhood information
- cluster ensemble
- similarity matrix
- density function
- gaussian mixture model
- high dimensional data
- unsupervised learning
- maximum likelihood