Table 3 Performance of the proposed XAI-CKD model and another traditional machine learning models.
From: Improved CKD classification based on explainable artificial intelligence with extra trees and BBFS
Models | Accuracy | Sensitivity | Specificity | F-score | AUC |
|---|---|---|---|---|---|
XAI-CKD | 99.9% | 99.9% | 99.9% | 99.9% | 1.000 |
RF | 97.5% | 97.5% | 97.5% | 97.4% | 0.968 |
DT | 95.8% | 95.8% | 95.8% | 95.8% | 0.955 |
BC | 94.1% | 94.1% | 94.2% | 94.1% | 0.936 |
AdaBoost | 85% | 85% | 85.2% | 85.3% | 0.862 |
KNN | 66.6% | 66.7% | 66.7% | 66.6% | 0.673 |
