PF-SMOTE: A novel parameter-free SMOTE for imbalanced datasets.
Qiong ChenZhong-Liang ZhangWenpo HuangJian WuXing-Gang LuoPublished in: Neurocomputing (2022)
Keyphrases
- imbalanced datasets
- parameter free
- class distribution
- imbalanced data
- cost sensitive learning
- class imbalance
- sampling methods
- ensemble methods
- training dataset
- decision trees
- outlier detection
- categorical data
- fraud detection
- cost sensitive
- fully automatic
- feature selection algorithms
- minority class
- training set
- imbalanced data sets
- highly skewed
- feature selection
- misclassification costs
- cluster analysis
- multi class
- support vector machine
- data analysis
- clustering algorithm