SCUT: Multi-Class Imbalanced Data Classification using SMOTE and Cluster-based Undersampling.
Astha AgrawalHerna L. ViktorEric PaquetPublished in: KDIR (2015)
Keyphrases
- multi class
- imbalanced data classification
- class imbalance
- cost sensitive
- minority class
- class distribution
- feature selection
- binary classification
- cost sensitive learning
- support vector machine
- misclassification costs
- active learning
- pairwise
- high dimensionality
- binary classifiers
- base classifiers
- sampling methods
- concept drift
- multi class classification
- training data
- similarity measure
- classification error
- test data
- training samples
- feature set
- feature space
- feature vectors