Improving Evolutionary Algorithm Performance for Feature Selection in High-Dimensional Data.
Nicole Dalia CiliaClaudio De StefanoFrancesco FontanellaAlessandra Scotto di FrecaPublished in: EvoApplications (2018)
Keyphrases
- high dimensional data
- evolutionary algorithm
- high dimensionality
- dimensionality reduction
- feature selection
- dimension reduction
- low dimensional
- data sets
- high dimensional
- subspace clustering
- high dimensions
- gene expression data
- multi objective
- data points
- nearest neighbor
- similarity search
- feature space
- data analysis
- input space
- original data
- missing values
- data distribution
- small sample size
- high dimensional spaces
- high dimensional data sets
- manifold learning
- clustering high dimensional data
- nonlinear dimensionality reduction
- feature extraction
- linear discriminant analysis
- text categorization
- variable selection
- sparse representation
- support vector
- genetic algorithm
- machine learning
- dimensional data
- model selection
- principal component analysis
- selected features
- text data
- subspace learning
- lower dimensional
- feature selection algorithms
- text classification
- variable weighting