Development of a machine learning-based model for predicting postoperative survival in gastric cancer

Figure 3 Comparative analysis of the performance of the ten machine learning models. A: Receiver operating characteristic curves for the training set; B: Receiver operating characteristic curves for the validation set; C: Calibration curves for the training set; D: Calibration curves for the validation set; E: Decision curve analysis for the training set; F: Decision curve analysis for the validation set. LR: Logistic regression; AUC: Area under the curve; CI: Confidence interval; RF: Random forest; MLP: Multi-layer perceptron; SVM: Support vector machine; XGBoost: Extreme gradient boosting; LGBM: Light gradient boosting machine; DT: Decision tree; GB: Gradient boosting; KNN: K-nearest neighbors; ET: Extremely randomized trees.