A DBN-based resampling SVM ensemble learning paradigm for credit classification with imbalanced data.
Lean YuRongtian ZhouLing TangRongda ChenPublished in: Appl. Soft Comput. (2018)
Keyphrases
- imbalanced data
- ensemble learning
- ensemble classifier
- generalization ability
- ensemble methods
- support vector machine
- support vector machine svm
- random forest
- base classifiers
- feature selection
- classification models
- decision trees
- svm classifier
- support vector
- machine learning methods
- minority class
- class distribution
- classification algorithm
- base learners
- random forests
- benchmark datasets
- class imbalance
- concept drift
- feature extraction
- decision boundary
- prediction accuracy
- multi class
- training samples
- classification accuracy
- training set
- feature set
- cost sensitive
- linear regression
- feature subset
- class labels