Constraint relaxation, cost-sensitive learning and bagging for imbalanced classification problems with outliers.
Talayeh RazzaghiPetros XanthopoulosOnur SerefPublished in: Optim. Lett. (2017)
Keyphrases
- cost sensitive learning
- constraint relaxation
- imbalanced data
- class imbalance
- imbalanced datasets
- minority class
- class distribution
- constraint satisfaction
- cost sensitive
- missing values
- misclassification costs
- base classifiers
- decision trees
- constraint optimization
- ensemble methods
- active learning
- missing data
- machine learning
- data points
- multi class problems
- ensemble learning
- probability estimation
- binary classification
- constraint satisfaction problems
- rule extraction
- multi class
- random forests
- unlabeled data
- training set
- high dimensionality
- constraint programming
- sampling methods
- base learners
- feature selection
- concept drift
- training data
- high dimensional
- single class
- neural network
- test set