DEA based dimensionality reduction for classification problems satisfying strict non-satiety assumption.
Parag C. PendharkarMarvin D. TrouttPublished in: Eur. J. Oper. Res. (2011)
Keyphrases
- dimensionality reduction
- data envelopment analysis
- feature extraction
- low dimensional
- high dimensional
- principal components
- data representation
- high dimensional data
- pattern recognition and machine learning
- random projections
- data points
- principal component analysis
- feature space
- linear discriminant analysis
- structure preserving
- preprocessing step
- manifold learning
- neural network
- intrinsic dimensionality
- dimensionality reduction methods
- case study
- lower dimensional
- principal components analysis
- kernel learning
- nonlinear dimensionality reduction
- similarity measure
- pattern recognition
- linear dimensionality reduction
- sparse representation