Exploiting Prototypical Explanations for Undersampling Imbalanced Datasets.
Yusuf ArslanKevin AllixClément LefebvreAndrey BoytsovTegawendé F. BissyandéJacques KleinPublished in: ICMLA (2022)
Keyphrases
- imbalanced datasets
- class imbalance
- majority class
- class distribution
- cost sensitive learning
- learning from imbalanced data
- sampling methods
- cost sensitive
- active learning
- minority class
- imbalanced data
- concept drift
- training dataset
- decision trees
- ensemble methods
- feature selection
- data sets
- support vector machine
- high dimensionality
- feature selection algorithms
- training set
- learning algorithm