Keyphrases
- dimensionality reduction
- principal component analysis
- high dimensional
- data representation
- high dimensional data
- feature extraction
- pattern recognition
- low dimensional
- principal components
- structure preserving
- lower dimensional
- high dimensionality
- feature selection
- nonlinear dimensionality reduction
- manifold learning
- linear discriminant analysis
- data points
- random projections
- feature space
- input space
- preprocessing step
- linear dimensionality reduction
- euclidean distance
- pattern recognition and machine learning
- dimensionality reduction methods
- singular value decomposition
- multidimensional scaling
- diffusion maps
- supervised dimensionality reduction
- linear projection
- data sets
- face recognition
- locally linear embedding
- kernel pca
- principal components analysis
- sparse representation