Feature selection for high-dimensional data.
Verónica Bolón-CanedoNoelia Sánchez-MaroñoAmparo Alonso-BetanzosPublished in: Prog. Artif. Intell. (2016)
Keyphrases
- high dimensional data
- feature selection
- high dimensionality
- dimensionality reduction
- dimension reduction
- high dimensional
- low dimensional
- nearest neighbor
- gene expression data
- subspace clustering
- similarity search
- data points
- high dimensions
- variable selection
- data sets
- manifold learning
- clustering high dimensional data
- data analysis
- feature space
- feature extraction
- data distribution
- linear discriminant analysis
- original data
- high dimensional spaces
- feature set
- dimensional data
- input space
- high dimensional datasets
- feature selection algorithms
- sparse representation
- selected features
- subspace learning
- text data
- machine learning
- neural network
- preprocessing step
- principal component analysis
- text classification
- text categorization
- data mining
- nonlinear dimensionality reduction
- feature subset
- microarray data
- lower dimensional
- support vector machine
- locally linear embedding
- small sample size
- high dimensional data sets
- informative features
- model selection