Rough set-based feature selection for credit risk prediction using weight-adjusted boosting ensemble method.
E. SivasankarC. SelviS. MahalakshmiPublished in: Soft Comput. (2020)
Keyphrases
- ensemble methods
- prediction accuracy
- credit risk
- feature selection
- ensemble classifier
- ensemble learning
- feature subset
- credit risk evaluation
- base classifiers
- rotation forest
- random forest
- credit scoring
- evaluation method
- risk analysis
- benchmark datasets
- generalization ability
- base learners
- machine learning methods
- decision trees
- feature extraction
- feature space
- support vector
- text classification
- rough set theory
- multi class
- classification accuracy
- support vector machine
- machine learning
- fraud detection
- classification models
- prediction model
- text categorization
- evaluation model
- exchange rate
- logistic regression
- financial data
- artificial neural networks
- model selection
- data mining