A genetic algorithm to optimize SMOTE and GAN ratios in class imbalanced datasets.
Hwi-Yeon ChoYong-Hyuk KimPublished in: GECCO Companion (2020)
Keyphrases
- imbalanced datasets
- genetic algorithm
- cost sensitive learning
- class distribution
- learning from imbalanced data
- imbalanced data
- class imbalance
- ensemble methods
- minority class
- sampling methods
- majority class
- decision trees
- training dataset
- highly skewed
- cost sensitive
- feature selection algorithms
- neural network
- training data
- genetic algorithm ga
- training set
- misclassification costs
- missing data
- prediction accuracy
- machine learning
- dimensionality reduction
- support vector machine