Nonnegative Laplacian embedding guided subspace learning for unsupervised feature selection.
Yong ZhangQi WangDun-Wei GongXianfang SongPublished in: Pattern Recognit. (2019)
Keyphrases
- subspace learning
- unsupervised feature selection
- graph embedding
- dimensionality reduction
- sparse coding
- low dimensional
- data representation
- feature selection
- principal component analysis
- nonnegative matrix factorization
- data clustering
- sparse representation
- manifold learning
- unsupervised learning
- high dimensional data
- semi supervised
- high dimensional
- data matrix
- pattern recognition
- high dimensionality
- face recognition
- natural images
- feature extraction
- data points
- image classification
- dimension reduction
- generative model
- spectral clustering
- object recognition
- original data
- matrix factorization
- linear discriminant analysis
- negative matrix factorization
- linear combination
- feature space
- data sets