High dimensional data classification and feature selection using support vector machines.
Bissan GhaddarJoe Naoum-SawayaPublished in: Eur. J. Oper. Res. (2018)
Keyphrases
- high dimensional data
- high dimensionality
- feature selection
- dimensionality reduction
- dimension reduction
- high dimensional
- low dimensional
- small sample size
- nearest neighbor
- feature space
- data sets
- feature extraction
- similarity search
- data points
- classification accuracy
- subspace clustering
- feature set
- high dimensions
- pattern recognition
- regression problems
- text classification
- data analysis
- high dimensional spaces
- high dimensional feature spaces
- multivariate temporal data
- feature selection algorithms
- input space
- nonlinear dimensionality reduction
- gene expression data
- support vector machine
- dimensional data
- dimensionality reduction methods
- manifold learning
- missing values
- machine learning
- text categorization
- principal component analysis
- variable selection
- clustering high dimensional data
- support vector
- lower dimensional
- high dimensional datasets
- locally linear embedding
- unsupervised learning
- decision trees
- microarray data
- sparse representation
- training data
- feature subset
- image processing
- linear discriminant analysis
- microarray
- real world
- database