GUM: A Guided Undersampling Method to Preprocess Imbalanced Datasets for Classification.
Kisuk SungW. Eric BrownErick Moreno-CentenoYu DingPublished in: CASE (2022)
Keyphrases
- class imbalance
- support vector machine svm
- classification accuracy
- support vector machine
- feature set
- machine learning
- pattern classification
- imbalanced datasets
- feature selection
- cost sensitive learning
- feature vectors
- error rate
- training process
- machine learning methods
- training samples
- sampling methods
- decision rules
- multi class
- active learning
- support vector
- learning algorithm