A clustering-based adaptive undersampling ensemble method for highly unbalanced data classification.
Xiaohan YuanChuan SunShuyu ChenPublished in: Appl. Soft Comput. (2024)
Keyphrases
- unbalanced data
- ensemble methods
- machine learning methods
- decision trees
- generalization ability
- benchmark datasets
- support vector machine
- training data
- ridge regression
- random forests
- image classification
- feature extraction
- pattern recognition
- imbalanced data
- ensemble classifier
- feature selection
- random forest
- text classification
- classification accuracy
- cross validation
- machine learning algorithms
- training set
- base learners
- ensemble learning
- machine learning
- support vector
- pairwise
- multiple kernel learning
- class imbalance
- text data
- prediction accuracy
- multi class
- supervised learning
- base classifiers
- classification models
- classification algorithm
- data sets