Improvement of Random Undersampling to Avoid Excessive Removal of Points from a Given Area of the Majority Class.
Malgorzata BachAleksandra WernerPublished in: ICCS (3) (2021)
Keyphrases
- majority class
- class imbalance
- class distribution
- attribute selection
- minority class
- imbalanced data
- training set
- imbalanced datasets
- active learning
- cost sensitive
- misclassification costs
- training instances
- data points
- decision boundary
- cost sensitive learning
- nearest neighbour
- convex hull
- training data
- data sets
- learning algorithm