Fig. 4. The performance of the four machine learning models.

a Classification performance on dataset 1 using five-fold cross-validation (n = 5 experiments for each model). For each, 80% of patients were used as the training set and the remaining patients were used as the internal validation set. b Receiver operating characteristics curves for classifying TFE3-RCC and ccRCC in the external validation set (dataset 2). Models were trained using dataset 1 and evaluated using dataset 2. The 95% confidence intervals for the AUC: LR (0.763–0.984), RF (0.736–0.960), SVM-L (0.725–0.959), and SVM-G (0.797–0.991). LR, logistic regression; RF, random forest; SVM-L, SVM with linear kernel; SVM-G, SVM with Gaussian kernel. Data are represented as mean ± SD in a.