Subspace Learning for Feature Selection via Rank Revealing QR Factorization: Unsupervised and Hybrid Approaches with Non-negative Matrix Factorization and Evolutionary Algorithm.
Amir MoslemiArash AhmadianPublished in: CoRR (2022)
Keyphrases
- subspace learning
- negative matrix factorization
- hybrid approaches
- evolutionary algorithm
- unsupervised feature selection
- singular value decomposition
- principal component analysis
- dimensionality reduction
- sparse representation
- feature selection
- matrix factorization
- tensor factorization
- low rank approximation
- unsupervised learning
- nonnegative matrix factorization
- dimension reduction
- sparse coding
- feature space
- semi supervised
- feature extraction
- low rank
- low dimensional
- face recognition
- data representation
- document clustering
- manifold learning
- latent semantic space
- text categorization
- collaborative filtering
- high dimensional data
- machine learning
- signal processing
- image processing
- pairwise
- support vector machine
- text classification
- linear discriminant analysis
- semi supervised learning
- image classification
- missing data
- data points
- data clustering
- discriminant analysis
- image patches
- supervised learning
- neural network
- image retrieval
- learning algorithm