Automatic selection of clustering algorithms using supervised graph embedding.
Noy Cohen-ShapiraLior RokachPublished in: CoRR (2020)
Keyphrases
- automatic selection
- graph embedding
- semi supervised
- clustering algorithm
- label information
- discriminant analysis
- supervised learning
- low dimensional
- dimensionality reduction
- semi supervised learning
- unsupervised learning
- data clustering
- k means
- cluster analysis
- labeled data
- data representation
- discriminant embedding
- subspace learning
- active learning
- document clustering
- learning algorithm
- feature representation
- pairwise
- clustering method
- high dimensional
- computer vision
- manifold learning
- spectral clustering
- geometric structure
- linear discriminant analysis
- geometric properties
- generative model
- pairwise constraints
- principal component analysis
- feature extraction