Keyphrases
- dimensionality reduction
- feature selection
- high dimensionality
- feature extraction
- high dimensional data
- class separability
- principal component analysis
- high dimensional
- input space
- preprocessing step
- data representation
- manifold learning
- dimensionality reduction methods
- feature space
- low dimensional
- unsupervised learning
- data points
- machine learning
- pattern recognition
- classification accuracy
- random projections
- principal components
- subspace learning
- support vector
- pattern recognition and machine learning
- text classification
- feature set
- kernel pca
- linear discriminant
- mutual information
- linear discriminant analysis
- dimension reduction
- dealing with high dimensional data
- linear dimensionality reduction
- nearest neighbor
- structure preserving
- nonlinear dimensionality reduction
- irrelevant features
- multi task
- method for feature selection
- feature weighting
- lower dimensional
- selected features
- feature subset
- feature selection algorithms
- supervised dimensionality reduction
- text categorization
- multi class
- microarray data
- feature ranking
- classification models
- metric learning