Sparse feature selection: Relevance, redundancy and locality structure preserving guided by pairwise constraints.
Zahir NoorieFatemeh AfsariPublished in: Appl. Soft Comput. (2020)
Keyphrases
- structure preserving
- pairwise constraints
- feature selection
- dimensionality reduction
- semi supervised
- pairwise
- data representation
- semi supervised clustering
- metric learning
- spectral clustering
- loss function
- high dimensional
- labeled data
- unlabeled data
- sparse representation
- classification accuracy
- feature extraction
- text categorization
- feature set
- text classification
- support vector
- decision boundary
- document clustering
- information retrieval
- unsupervised learning
- multi task
- semi supervised learning
- machine learning
- relevance feedback
- multi class
- support vector machine
- constrained clustering
- feature subset
- data sets
- training data