A multi-class boosting method for learning from imbalanced data.
Xiaohui YuanMohamed AbouelenienPublished in: Int. J. Granul. Comput. Rough Sets Intell. Syst. (2015)
Keyphrases
- multi class
- learning from imbalanced data
- imbalanced datasets
- imbalanced data
- random forest
- support vector machine
- cost sensitive
- base classifiers
- cost sensitive learning
- pairwise
- class distribution
- decision trees
- linear classifiers
- multi class classification
- binary classification
- misclassification costs
- feature selection
- ensemble methods
- machine learning
- feature selection algorithms
- learning algorithm