Multivariate Direction Scoring for Dimensionality Reduction in Classification Problems.
Giorgio BiagettiPaolo CrippaLaura FalaschettiSimone OrcioniClaudio TurchettiPublished in: KES-IDT (1) (2016)
Keyphrases
- dimensionality reduction
- high dimensional data
- data representation
- feature extraction
- high dimensional
- data points
- principal component analysis
- pattern recognition
- low dimensional
- pattern recognition and machine learning
- dimensionality reduction methods
- feature space
- structure preserving
- nonlinear dimensionality reduction
- random projections
- high dimensionality
- dimension reduction
- sparse representation
- regression model
- linear discriminant analysis
- multivariate data
- multidimensional scaling
- input space
- lower dimensional
- feature selection
- intrinsic dimensionality
- principal components analysis
- statistical tests
- manifold learning
- principal components
- singular value decomposition
- euclidean distance
- locally linear embedding
- pairwise
- decision trees
- information retrieval