A cost-sensitive active learning algorithm: toward imbalanced time series forecasting.
Jing ZhangQun DaiPublished in: Neural Comput. Appl. (2022)
Keyphrases
- cost sensitive
- class imbalance
- learning algorithm
- class distribution
- active learning
- misclassification costs
- cost sensitive learning
- multi class
- boosting algorithms
- cost sensitive classification
- binary classification
- naive bayes
- base learners
- training data
- fraud detection
- machine learning
- unlabeled data
- machine learning algorithms
- minority class
- classification algorithm
- learning tasks
- training examples
- support vector machine
- learning process
- supervised learning
- generalization error
- test set
- error rate
- training samples
- markov random field
- upper bound
- imbalanced data
- confidence weighted
- cost sensitive boosting