Iterative minority oversampling and its ensemble for ordinal imbalanced datasets.
Ning WangZhong-Liang ZhangXing-Gang LuoPublished in: Eng. Appl. Artif. Intell. (2024)
Keyphrases
- imbalanced datasets
- minority class
- imbalanced data
- majority class
- ensemble learning
- class imbalance
- class distribution
- ensemble methods
- learning from imbalanced data
- training set
- classification error
- cost sensitive learning
- training data
- base learners
- base classifiers
- nearest neighbour
- imbalanced class distribution
- active learning
- sampling methods
- support vector machine
- decision boundary
- random forest
- generalization ability
- cost sensitive
- decision trees
- feature selection
- neural network
- original data
- training dataset
- concept drift
- prediction accuracy
- meta learning
- learning scheme
- random forests
- test set
- nearest neighbor
- classification accuracy
- machine learning
- data sets