I am using random forest model for an imbalanced dataset. The dependent variable is Yes=73, No=7100. I have 65 independent variables both factor and numeric. I have tried to develop models for imbalanced, undersampling, oversampling and Smote sampling. However, the model performance is not showing any significant improvement or difference Here is the summary
- Using Unbalanced Data: precision: 1.000 recall: 1.000 F: 0.500, AUC: 1.000
- Using Under-sampling precision: 0.615 recall: 1.000 F: 0.381 AUC: 1.000
- Using Oversampling precision: 1.000, recall: 1.000 F: 0.500 AUC: 1.000
- USing SMOTE: precision: 0.941 recall: 1.000 F: 0.485 AUC: 1.000
Did I do something terribly wrong? What does the result mean?