Table 2 Performance of the models
Models | Bacteria | Accuracy | Brier Score | Precision | Recall | F1 Score |
|---|---|---|---|---|---|---|
KNN | Enterobacteriaceae | 0.775 (0.674, 0.857)* | 0.449 | 1.000 | 0.638 | 0.779 |
Staphylococcus | 0.500 | 0.833 | 0.625 | |||
Monosodium | 0.777 | 0.875 | 0.823 | |||
Streptococcus | 0.625 | 0.833 | 0.714 | |||
Other Bacilli | 0.750 | 0.750 | 0.750 | |||
Enterococcus | 1.000 | 1.000 | 1.000 | |||
Fungus | 0.857 | 1.000 | 0.923 | |||
Boosted Logistic Regression | Enterobacteriaceae | 0.838 (0.723, 0.919)* | 0.460 | 0.900 | 0.818 | 0.857 |
Staphylococcus | 0.692 | 0.818 | 0.750 | |||
Monosodium | 0.900 | 0.818 | 0.857 | |||
Streptococcus | 1.000 | 1.000 | 1.000 | |||
Other Bacilli | 0.750 | 0.600 | 0.666 | |||
Enterococcus | 0.833 | 1.000 | 0.909 | |||
Fungus | 0.833 | 1.000 | 0.909 | |||
Random Forest | Enterobacteriaceae | 0.865 (0.776, 0.928)* | 0.221 | 0.966 | 0.805 | 0.878 |
Staphylococcus | 0.631 | 1.000 | 0.774 | |||
Monosodium | 0.777 | 0.875 | 0.823 | |||
Streptococcus | 1.000 | 0.833 | 0.909 | |||
Other Bacilli | 1.000 | 0.750 | 0.857 | |||
Enterococcus | 1.000 | 1.000 | 1.000 | |||
Fungus | 1.000 | 1.000 | 1.000 | |||
Gradient Boosting Machine | Enterobacteriaceae | 0.910 (0.830, 0.960)* | 0.214 | 0.944 | 0.944 | 0.944 |
Staphylococcus | 0.733 | 0.916 | 0.814 | |||
Monosodium | 0.875 | 0.875 | 0.875 | |||
Streptococcus | 1.000 | 0.833 | 0.909 | |||
Other Bacilli | 1.000 | 0.750 | 0.857 | |||
Enterococcus | 1.000 | 1.000 | 1.000 | |||
Fungus | 1.000 | 1.000 | 1.000 |