An ensemble contrastive classification framework for imbalanced learning with sample-neighbors pair construction.
Xin GaoXin JiaJing LiuBing XueZijian HuangShiyuan FuGuangyao ZhangKangsheng LiPublished in: Knowl. Based Syst. (2022)
Keyphrases
- supervised learning
- learning algorithm
- multi category
- learning scheme
- unsupervised learning
- incremental learning
- probabilistic model
- active learning
- learning process
- classification accuracy
- support vector
- reinforcement learning
- multi task
- decision trees
- kernel learning
- random forests
- neural network
- learning from imbalanced data
- training set
- feature vectors
- ensemble classifier
- feature extraction
- training data
- imbalanced datasets
- imbalanced data
- binary classification problems
- learning phase
- base learners
- classification algorithm
- regression problems
- class imbalance
- data points
- support vector machine
- text classification
- learning tasks
- machine learning methods