Multi-objective optimization of base classifiers in StackingC by NSGA-II for intrusion detection.
Michael MillikenYaxin BiLeo GalwayGlenn I. HawePublished in: SSCI (2016)
Keyphrases
- intrusion detection
- base classifiers
- multi objective optimization
- nsga ii
- multi objective
- multi class
- ensemble methods
- evolutionary algorithm
- pareto optimal
- decision trees
- multiobjective optimization
- anomaly detection
- multi objective optimization problems
- training set
- naive bayes
- multi objective optimisation
- multiple objectives
- genetic algorithm
- bi objective
- constrained multi objective optimization problems
- pareto dominance
- cost sensitive
- multi objective genetic algorithm
- training samples
- class labels
- differential evolution
- multi objective evolutionary algorithms
- data mining
- objective function
- feature set
- particle swarm optimization
- feature selection
- multi objective problems
- optimization problems
- optimization algorithm
- pareto frontier
- test problems
- strength pareto evolutionary algorithm
- support vector
- pareto optimal solutions
- knowledge discovery
- search algorithm
- feature space
- crossover operator
- search space
- cost function
- pareto optimal set
- classification accuracy