A survey of dimensionality reduction techniques.
Carlos Oscar Sánchez SorzanoJavier VargasAlberto Domingo Pascual-MontanoPublished in: CoRR (2014)
Keyphrases
- dimensionality reduction
- high dimensional
- principal component analysis
- feature space
- structure preserving
- high dimensional data
- low dimensional
- principal components
- manifold learning
- high dimensionality
- feature extraction
- pattern recognition
- input space
- linear discriminant analysis
- euclidean distance
- data representation
- feature selection
- kernel learning
- linear dimensionality reduction
- pattern recognition and machine learning
- data points
- singular value decomposition
- random projections
- nonlinear dimensionality reduction
- semi supervised
- dimension reduction
- metric learning
- dimensionality reduction methods
- intrinsic dimensionality
- graph embedding
- semi supervised dimensionality reduction
- computer vision
- linear projection
- face recognition
- multiscale
- pairwise
- principal components analysis
- preprocessing step
- feature vectors