Imbalanced datasets in the generation of fuzzy classification systems - an investigation using a multiobjective evolutionary algorithm based on decomposition.
Edward Hinojosa CárdenasHeloisa A. CamargoYván J. TúpacPublished in: FUZZ-IEEE (2016)
Keyphrases
- classification systems
- imbalanced datasets
- multiobjective evolutionary algorithm
- multi objective
- multiobjective optimization
- cost sensitive learning
- class distribution
- ensemble methods
- fuzzy sets
- fuzzy logic
- nsga ii
- class imbalance
- decision trees
- sampling methods
- training dataset
- fuzzy rules
- cost sensitive
- optimization algorithm
- feature selection algorithms
- artificial immune system
- imbalanced data
- neural network
- cost function
- artificial neural networks
- machine learning methods
- training set
- metaheuristic
- machine learning