Table 4 Performance metrics of models after ROS and dimensionality reduction.
From: Enhanced cervical cancer diagnosis using a novel Bayesian fusion ensemble method with explainable AI
Model name | Class | Precision | Recall | F1-value |
|---|---|---|---|---|
Random Forest | 0 1 | 1.00 0.99 | 0.99 1.00 | 1.00 1.00 |
Decision Tree | 0 1 | 1.00 0.97 | 0.98 1.00 | 0.99 0.99 |
Naïve Bayes | 0 1 | 0.93 0.82 | 0.84 0.92 | 0.88 0.87 |
ANN | 0 1 | 1.00 0.94 | 0.95 1.00 | 0.97 0.97 |
XGBoost | 0 1 | 1.00 0.95 | 0.96 1.00 | 0.98 0.98 |
K-NN | 0 1 | 1.00 0.94 | 0.95 1.00 | 0.97 0.97 |
Proposed model | 0 1 | 1.00 0.99 | 1.00 1.00 | 0.99 1.00 |
