An approach to class imbalance problem based on stacking and inverse random under sampling methods.
Yuwei ZhangGuanjun LiuWenjing LuanChungang YanChangjun JiangPublished in: ICNSC (2018)
Keyphrases
- sampling methods
- class imbalance
- class distribution
- active learning
- imbalanced datasets
- cost sensitive
- cost sensitive learning
- concept drift
- high dimensionality
- feature selection
- imbalanced data
- minority class
- random sampling
- base classifiers
- data sets
- class labels
- multi class
- support vector machine
- training data
- machine learning