Imbalanced Resampling using SMOTE with Boosting (SMOTEWB)
Adaptive Synthetic Sampling
Borderline Synthetic Minority Oversampling Technique
Geometric Synthetic Minority Oversamplnig Technique (GSMOTE)
Random Oversampling (ROS)
Randomly Over Sampling Examples
Relocating safe-level SMOTE with minority outcast handling
Random Undersampling (RUS)
Random Walk Oversampling (SMOTE)
Safe-level Synthetic Minority Oversampling Technique
Synthetic Minority Oversampling Technique (SMOTE)
SMOTE with boosting (SMOTEWB)
Provides the SMOTE with Boosting (SMOTEWB) algorithm. See F. Sağlam, M. A. Cengiz (2022) <doi:10.1016/j.eswa.2022.117023>. It is a SMOTE-based resampling technique which creates synthetic data on the links between nearest neighbors. SMOTEWB uses boosting weights to determine where to generate new samples and automatically decides the number of neighbors for each sample. It is robust to noise and outperforms most of the alternatives according to Matthew Correlation Coefficient metric. Alternative resampling methods are also available in the package.