Solving Imbalanced Data in Credit Risk Prediction: A Comparison of Resampling Strategies for Different Machine Learning Classification Algorithms, Taking Threshold Tuning into Account.
Chenyu YangYanjie DongJiachen LuZherui PengPublished in: MLMI (2022)
Keyphrases
- machine learning
- imbalanced data
- machine learning algorithms
- learning algorithm
- pattern recognition
- support vector machine
- credit risk
- ensemble classifier
- machine learning methods
- decision trees
- feature selection
- classification algorithm
- classification accuracy
- benchmark datasets
- class imbalance
- prediction accuracy
- image classification
- text classification
- support vector machine svm
- sampling methods
- feature vectors
- supervised learning
- random forest
- classification models
- data mining
- knowledge discovery
- multi class
- generalization ability
- evaluation method
- support vector
- svm classifier
- active learning
- data analysis
- model selection