A meta-heuristic feature selection algorithm combining random sampling accelerator and ensemble using data perturbation.
Shuaishuai ZhangKeyu LiuTaihua XuXibei YangAo ZhangPublished in: Appl. Intell. (2023)
Keyphrases
- random sampling
- metaheuristic
- feature selection algorithms
- data perturbation
- feature selection
- privacy preserving data mining
- active learning
- simulated annealing
- optimization problems
- optimal solution
- privacy preserving
- random projections
- sampling algorithm
- sample size
- statistical databases
- genetic algorithm
- search space
- sampling methods
- optimization method
- data sets
- neural network
- particle swarm optimization
- selection algorithm
- feature subset
- feature set
- sliding window
- evolutionary algorithm
- data privacy
- ensemble methods
- learning algorithm
- genetic programming
- support vector
- feature space
- learning models
- artificial neural networks
- training set
- search algorithm
- objective function
- base classifiers
- dimension reduction
- database