Table 9 Statistics by the class of different classifiers with bank marketing dataset
From: Selecting critical features for data classification based on machine learning methods
Method | Accuracy | Precision | Recall | Features |
|---|---|---|---|---|
RF + SVM | 0.89 | 0.9137 | 0.9791 | 7 |
RF + LDA | 0.9 | 0.9226 | 0.9679 | 7 |
RF + KNN | 0.886 | 0.9080 | 0.9691 | 7 |
RF + RF | 0.9099 | 0.9122 | 0.9810 | 7 |