A Modified Borderline Smote with Noise Reduction in Imbalanced Datasets.
M. RevathiD. RamyachitraPublished in: Wirel. Pers. Commun. (2021)
Keyphrases
- noise reduction
- imbalanced datasets
- class distribution
- cost sensitive learning
- signal to noise ratio
- imbalanced data
- class imbalance
- sampling methods
- decision trees
- ensemble methods
- noisy environments
- noise level
- edge detection
- training dataset
- feature selection algorithms
- highly skewed
- cost sensitive
- fraud detection
- linear regression
- minority class
- training data
- misclassification costs
- prediction accuracy
- image processing
- computer vision