fGAAM: A fast and resizable genetic algorithm with aggressive mutation for feature selection.
Izabela RejerJaroslaw JankowskiPublished in: Pattern Anal. Appl. (2022)
Keyphrases
- genetic algorithm
- feature selection
- fitness function
- population size
- genetic operators
- crossover operator
- genetic algorithm ga
- evolutionary algorithm
- mutation operator
- parameter optimization
- evolutionary computation
- text categorization
- feature set
- mutual information
- simulated annealing
- text classification
- multi objective
- fuzzy logic
- genetic programming
- evolutionary process
- crossover and mutation
- differential evolution
- optimization method
- irrelevant features
- machine learning
- multi objective optimization
- feature selection algorithms
- unsupervised feature selection
- tabu search
- metaheuristic
- neural network
- support vector
- feature space
- high dimensionality
- redundant features
- feature extraction
- artificial immune system
- feature weighting
- discriminative features
- feature ranking
- multi class
- initial population
- adaptive mutation
- support vector machine
- search capabilities
- dimensionality reduction
- selected features
- ant colony optimization
- information gain