Table 6 Multiclass classification results without and with feature selection
From: Chronic kidney disease prediction using machine learning techniques
Models | No. of features | Acc | Prec | Rec | F1 | Sen | Spec |
|---|---|---|---|---|---|---|---|
RF | 18 | 78.3 | 79.5 | 77.4 | 77.3 | 77.4 | 94.5 |
RF with RFECV | 9 | 79.0 | 79.8 | 78.1 | 77.9 | 78.1 | 94.7 |
RF with UFS | 14 | 77.6 | 78.9 | 76.6 | 76.7 | 76.7 | 94.3 |
SVM | 18 | 63.0 | 60.9 | 61.5 | 59.9 | 61.6 | 90.6 |
SVM with RFECV | 10 | 62.2 | 58.7 | 60.7 | 56.5 | 60.8 | 90.5 |
SVM with UFS | 14 | 61.5 | 59.2 | 60.5 | 58.4 | 60.5 | 90.2 |
DT | 18 | 77.5 | 79.6 | 76.4 | 76.2 | 76.5 | 94.3 |
DT with RFECV | 7 | 78.0 | 80 | 76.9 | 76.6 | 76.9 | 94.4 |
DT with UFS | 14 | 77.9 | 79.8 | 76.7 | 76.4 | 76.7 | 94.4 |