An empirical comparison on state-of-the-art multi-class imbalance learning algorithms and a new diversified ensemble learning scheme.
Jingjun BiChongsheng ZhangPublished in: Knowl. Based Syst. (2018)
Keyphrases
- learning scheme
- class imbalance
- learning algorithm
- active learning
- base learners
- random subspaces
- imbalanced data
- minority class
- class distribution
- cost sensitive
- feature selection
- training data
- machine learning
- imbalanced datasets
- sampling methods
- imbalanced class distribution
- class noise
- concept drift
- training examples
- back propagation
- high dimensionality
- supervised learning
- learning process
- reinforcement learning
- learning problems
- unlabeled data
- multi class
- feature extraction
- generalization error
- random forest
- learning tasks
- classification algorithm
- labeled data