Discriminative sparse embedding based on adaptive graph for dimension reduction.
Zhonghua LiuKaiming ShiKaibing ZhangWeihua OuLin WangPublished in: Eng. Appl. Artif. Intell. (2020)
Keyphrases
- dimension reduction
- discriminative information
- high dimensional
- random projections
- manifold embedding
- feature extraction
- low dimensional
- sparse metric learning
- graph embedding
- unsupervised learning
- high dimensional problems
- principal component analysis
- manifold learning
- feature space
- feature selection
- high dimensionality
- high dimensional data
- singular value decomposition
- dimensionality reduction
- cluster analysis
- linear discriminant analysis
- variable selection
- semi supervised
- preprocessing
- locality preserving projections
- latent space
- partial least squares
- sparse representation
- sparse coding
- vector space
- model selection
- data analysis
- feature vectors
- data points
- pattern recognition
- dimension reduction methods
- high dimensional data analysis