An empirical evaluation on dimensionality reduction schemes for dissimilarity-based classifications.
Sang-Woon KimPublished in: Pattern Recognit. Lett. (2011)
Keyphrases
- dimensionality reduction
- high dimensionality
- high dimensional
- high dimensional data
- feature extraction
- principal components
- principal component analysis
- dimensionality reduction methods
- data representation
- input space
- empirical evaluation
- nonlinear dimensionality reduction
- manifold learning
- data points
- low dimensional
- random projections
- singular value decomposition
- feature space
- kernel learning
- lower dimensional
- structure preserving
- pattern recognition and machine learning
- preprocessing step
- pattern recognition
- pairwise
- principal components analysis
- multiscale
- locally linear embedding
- feature selection
- information systems
- linear dimensionality reduction
- databases