A comparative analysis of genetic algorithm and ant colony optimization to select attributes for an heterogeneous ensemble of classifiers.
Laura Emmanuella A. SantanaLigia SilvaAnne M. P. CanutoFernando PintroKarliane O. ValePublished in: IEEE Congress on Evolutionary Computation (2010)
Keyphrases
- ant colony optimization
- genetic algorithm
- ensemble learning
- metaheuristic
- ensemble classifier
- classifier ensemble
- training data
- aco algorithm
- ant colony
- swarm intelligence
- particle swarm optimization
- training set
- hybrid algorithm
- combinatorial optimization problems
- ant colony algorithm
- traveling salesman problem
- ant colony optimization algorithm
- neural network
- aco algorithms
- function optimization
- ensemble methods
- decision trees
- attribute values
- feature selection
- nature inspired
- learning classifier systems
- simulated annealing
- fuzzy logic
- classification algorithm
- particle swarm optimization pso
- evolutionary strategy
- mutation operator
- ant colonies
- tabu search
- multi objective
- artificial ants
- learning algorithm
- combinatorial optimization
- evolutionary computation
- artificial immune system
- fitness function
- feature set
- metaheuristic algorithms
- foraging behavior
- evolutionary algorithm
- search space
- artificial neural networks
- machine learning