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