Estimating Clusters Centres Using Support Vector Machine: An Improved Soft Subspace Clustering Algorithm.
Amel BoulemnadjelFella HachoufPublished in: CAIP (1) (2013)
Keyphrases
- clustering algorithm
- subspace clustering
- support vector machine
- subspace clusters
- overlapping clusters
- feature space
- clustering method
- data clustering
- fuzzy clustering
- multi class
- hierarchical clustering
- fuzzy c means
- cluster analysis
- k means
- principal components analysis
- svm classifier
- unsupervised clustering
- clustering approaches
- document clustering
- kernel function
- cluster centers
- feature vectors
- hierarchical clustering algorithm
- graph clustering
- clusters of arbitrary shapes
- arbitrary shape
- clustering framework
- density based clustering
- disjoint clusters
- classification method
- feature extraction
- feature selection
- subspace projections
- meaningful clusters
- agglomerative hierarchical clustering
- training data
- machine learning
- kernel methods
- support vector
- spatial clustering
- clustering quality
- clustering analysis
- principal component analysis
- high dimensional data
- support vector machine svm
- constrained clustering
- similarity matrix
- agglomerative clustering
- dense regions
- normalized cut
- cluster validation
- cluster labels
- affinity propagation
- dimensionality reduction
- high dimensional
- nearest neighbor
- cluster structure