Combining Random Subspace Approach with smote Oversampling for Imbalanced Data Classification.
Pawel KsieniewiczPublished in: HAIS (2019)
Keyphrases
- imbalanced data classification
- minority class
- class imbalance
- class distribution
- base learners
- ensemble learning
- classification error
- active learning
- cost sensitive learning
- decision boundary
- support vector machine
- decision trees
- feature selection
- learning scheme
- random forest
- cost sensitive
- learning tasks
- high dimensionality
- training dataset
- concept drift
- nearest neighbour
- training set
- training data
- random forests
- meta learning