Table 3 Performance evaluation of models using the test set. The standard deviation is reported in round brackets
From: Machine learning models predicting multidrug resistant urinary tract infections using “DsaaS”
Method | AUC-ROC | Accuracy | AUC-PRC | F1 score | MCC | Sensitivity | Specificity |
|---|---|---|---|---|---|---|---|
Catboost | 0.739 (0.021) | 0.717 (0.032) | 0.853 (0.028) | 0.809 (0.027) | 0.909 (0.026) | 0.904 (0.061) | 0.343 (0.052) |
SVM | 0.628 (0.025) | 0.630 (0.057) | 0.752 (0.031) | 0.702 (0.033) | 0.810 (0.032) | 0.823 (0.042) | 0.254 (0.085) |
NeuralNetworks | 0.652 (0.023) | 0.686 (0.019) | 0.801 (0.024) | 0.804 (0.016) | 0.878 (0.024) | 0.880 (0.077) | 0.288 (0.075) |