Table 2 The performance of five machine learning models in the training cohort
From: Identification of the immune-related biomarkers in Behcet’s disease by plasma proteomic analysis
Recall | Specificity | Precision | Accuracy | F1 score | AUC | |
|---|---|---|---|---|---|---|
Naive Bayes | 0.636 | 0.667 | 0.700 | 0.650 | 0.667 | 0.769 |
Support vector machine | 0.667 | 0.750 | 0.800 | 0.700 | 0.727 | 0.846 |
Extreme gradient boosting | 0.700 | 0.700 | 0.700 | 0.700 | 0.700 | 0.769 |
Random forest | 0.727 | 0.778 | 0.800 | 0.750 | 0.762 | 0.817 |
Neural network | 0.692 | 0.857 | 0.900 | 0.750 | 0.783 | 0.856 |