A cross-validation framework to find a better state than the balanced one for oversampling in imbalanced classification.
Qizhu DaiDonggen LiShuyin XiaPublished in: Int. J. Mach. Learn. Cybern. (2023)
Keyphrases
- cross validation
- model selection
- support vector
- class imbalance
- training set
- hyperparameters
- generalization error
- nearest neighbor classifiers
- regression problems
- variable selection
- cross validated
- unseen data
- information criterion
- classification accuracy
- binary classifiers
- bayesian framework
- roc analysis
- class labels
- kernel learning
- decision trees
- leave one out cross validation
- minority class
- svm classification
- probabilistic model
- class distribution
- machine learning
- svm classifier
- incremental learning