Modular Dimensionality Reduction.
Henry W. J. ReeveTingting MuGavin BrownPublished in: ECML/PKDD (1) (2018)
Keyphrases
- dimensionality reduction
- feature extraction
- low dimensional
- pattern recognition and machine learning
- high dimensional
- high dimensional data
- principal component analysis
- preprocessing step
- data representation
- high dimensionality
- data points
- principal components
- manifold learning
- linear discriminant analysis
- lower dimensional
- random projections
- feature selection
- modular neural networks
- singular value decomposition
- pattern recognition
- structure preserving
- feature space
- dimensionality reduction methods
- diffusion maps
- graph embedding
- linear projection
- semi supervised dimensionality reduction
- metric learning
- image sequences
- data sets
- principal components analysis
- locally linear embedding
- intrinsic dimensionality
- highly flexible
- spectral clustering
- active learning
- linear dimensionality reduction
- data analysis
- database