A simple plug-in bagging ensemble based on threshold-moving for classifying binary and multiclass imbalanced data.
Guillem CollellDrazen PrelecKaustubh R. PatilPublished in: Neurocomputing (2018)
Keyphrases
- imbalanced data
- multi class
- base classifiers
- support vector machine
- feature selection
- ensemble methods
- binary classifiers
- multiclass learning
- class distribution
- class imbalance
- binary classification problems
- ensemble learning
- binary classification
- ensemble classifier
- linear regression
- multiclass problems
- cost sensitive
- random forest
- decision trees
- svm classifier
- pairwise
- multi class classification
- classification models
- sampling methods
- minority class
- random forests
- classification error
- meta learning
- decision boundary
- active learning
- support vector machine svm
- generalization ability
- regression problems
- base learners
- high dimensionality
- benchmark datasets
- learning algorithm