A supervised take on dimensionality reduction via hybrid subset selection.
Javad RahimikolluJishnu DasPublished in: Patterns (2022)
Keyphrases
- subset selection
- dimensionality reduction
- feature selection
- unsupervised learning
- supervised dimensionality reduction
- label information
- hill climbing
- high dimensionality
- data representation
- discriminant projection
- high dimensional data
- neighborhood preserving embedding
- structure preserving
- feature extraction
- principal component analysis
- pattern recognition
- high dimensional
- dimensionality reduction methods
- low dimensional
- feature space
- lower dimensional
- unsupervised feature selection
- pattern recognition and machine learning
- subspace learning
- semi supervised
- nonlinear dimensionality reduction
- text categorization
- lower bound
- supervised learning
- graph embedding
- linear discriminant analysis
- special case
- support vector machine
- manifold learning
- principal components
- search space