Table 9 Results of the test dataset for the new primary model
Particular | Data | ||
|---|---|---|---|
Model name | New primary | ||
No. of samples | 311 | 311 | 311 |
Total number of features | 388 | 388 | 388 |
ML algorithm used | Random Forest | KSVM | XGBoost |
Feature selection technique | SFFS | SFFS | SFFS |
OverSampling method used | SMOTE | SMOTE | SMOTE |
No. of samples after OverSampling | 588 | 588 | 588 |
Number of synthetic samples | 277 | 277 | 277 |
No. of features used in the dataset | 20 | 42 | 18 |
Mean accuracy train | 0.99 | 1 | 1 |
Mean accuracy test | 0.91 | 0.98 | 0.90 |
Sensitivity | 0.88 | 1.00 | 0.88 |
Specificity | 0.91 | 0.98 | 0.91 |
Mean F-Score train label 0 | 1 | 1 | 1 |
Mean F-Score train label 1 | 1 | 1 | 1 |
Mean F-score test label 0 | 0.95 | 0.98 | 0.94 |
Mean F-score test label 1 | 0.63 | 0.95 | 0.53 |
No. of samples for class-0 | 294 | 294 | 294 |
No. of samples for class-1 | 17 | 17 | 17 |
Base algorithm | Random forest | KSVM | XGBoost |
ROC_AUC_Score | 0.95 | 0.99 | 0.95 |