Improvement of Bagging performance for classification of imbalanced datasets using evolutionary multi-objective optimization.
Seyed Ehsan RoshanShahrokh AsadiPublished in: Eng. Appl. Artif. Intell. (2020)
Keyphrases
- imbalanced datasets
- imbalanced data
- evolutionary multi objective optimization
- decision trees
- ensemble methods
- class imbalance
- learning from imbalanced data
- class distribution
- cost sensitive learning
- machine learning
- classification accuracy
- sampling methods
- benchmark datasets
- feature selection
- support vector machine
- training set
- generalization ability
- cost sensitive
- random forest
- classification models
- pattern classification
- feature extraction
- prediction accuracy
- training dataset
- support vector
- minority class
- ensemble classifier
- binary classification
- feature selection algorithms
- support vector machine svm
- random forests
- linear regression
- multi class classification
- svm classifier
- probability estimation
- training samples
- model selection
- cross validation
- supervised learning
- classification rules
- high dimensionality
- genetic algorithm