A Multi-Schematic Classifier-Independent Oversampling Approach for Imbalanced Datasets.
Saptarshi BejKristian SchulzPrashant SrivastavaMarkus WolfienOlaf WolkenhauerPublished in: IEEE Access (2021)
Keyphrases
- imbalanced datasets
- minority class
- class imbalance
- majority class
- cost sensitive learning
- class distribution
- learning from imbalanced data
- highly skewed
- sampling methods
- imbalanced data
- decision boundary
- decision trees
- training dataset
- feature selection algorithms
- support vector machine
- training data
- nearest neighbour
- classification error
- feature selection
- active learning
- cost sensitive
- training set
- misclassification costs
- machine learning
- ensemble learning
- feature space
- feature set
- training samples
- training examples
- class labels
- original data
- binary classification
- probability estimation
- linear classifiers
- ensemble methods
- classification algorithm
- random forest
- rare class
- data sets