Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data.
Taghi M. KhoshgoftaarJason Van HulseAmri NapolitanoPublished in: IEEE Trans. Syst. Man Cybern. Part A (2011)
Keyphrases
- imbalanced data
- ensemble methods
- ensemble learning
- ensemble classifier
- base classifiers
- feature selection
- learning from imbalanced data
- random forest
- imbalanced datasets
- random forests
- linear regression
- class distribution
- prediction accuracy
- base learners
- decision trees
- benchmark datasets
- support vector machine
- classification models
- machine learning methods
- class imbalance
- decision boundary
- concept drift
- multi class
- training set