Cost-sensitive learning considering label and feature distribution consistency: A novel perspective for health prognosis of rotating machinery with imbalanced data.
Yudong CaoMinping JiaXiaoli ZhaoXiaoan YanKe FengPublished in: Expert Syst. Appl. (2024)
Keyphrases
- cost sensitive learning
- imbalanced data
- imbalanced datasets
- class imbalance
- class distribution
- minority class
- cost sensitive
- misclassification costs
- class labels
- active learning
- binary classification
- missing values
- decision trees
- multi label
- probability estimation
- feature selection
- ensemble methods
- high dimensionality
- feature set
- unlabeled data
- fault diagnosis
- training set
- sampling methods
- learning models
- concept drift
- training samples
- image classification
- base classifiers
- data distribution
- test set
- multi class
- naive bayes
- feature space
- linear regression