Effects of class imbalance on resampling and ensemble learning for improved prediction of cyanobacteria blooms.
Jihoon ShinSeonghyeon YoonYoungWoo KimTaeho KimByeongGeon GoYoonKyung ChaPublished in: Ecol. Informatics (2021)
Keyphrases
- ensemble learning
- software defect prediction
- class imbalance
- concept drift
- ensemble classifier
- ensemble methods
- class distribution
- prediction accuracy
- generalization ability
- minority class
- active learning
- cost sensitive
- imbalanced data
- unlabeled data
- base classifiers
- decision trees
- sampling methods
- learning algorithm
- random forest
- data sets
- prediction model
- classification algorithm
- semi supervised
- training data
- base learners
- feature selection
- sample selection bias
- machine learning