Table 3 Performances’ summary of Data-Level methods
From: A survey on addressing high-class imbalance in big data
| Technique | GM | TPR * TNR | AUC | Accuracy | F-measure | Big Data framework |
|---|---|---|---|---|---|---|
| Data-Sampling methods | ||||||
| Fernandez et al. [32] | Apache Hadoop and Apache Spark | |||||
| ROS | 0.71 | – | – | – | – | |
| RUS | 0.70 | – | – | – | – | |
| SMOTE | 0.63 | – | – | – | – | |
| Rio et al. [51] | Apache Hadoop | |||||
| ROS | – | 0.49 | – | – | – | |
| RUS | – | 0.48 | – | – | – | |
| Triguero et al. [16] | Apache Hadoop and Apache Spark | |||||
| EUS | 0.67 | – | 0.67 | – | – | |
| RUS | 0.66 | – | 0.66 | – | – | |
| Park et al. [54] | Apache Hadoop | |||||
| SMOTE | – | – | – | 0.76 | – | |
| Park and Ha [56] | Apache Hadoop | |||||
| SMOTE | – | – | – | 0.81 | – | |
| Chai et al. [57] | – | |||||
| RUS | – | – | – | – | 0.99 | |
