Fig. 2.

Machine learning-based gene signature for predicting metastatic status in breast cancer. a XGBoost, b decision tree, c support vector machine, d K-nearest neighbor, e logistic regression, and f random forest binary classifiers were used to establish the classification model. Tenfold cross-validation was performed for each model, and the receiver operating characteristic (ROC) curve was plotted to calculate the mean area under the ROC curve (AUC). The standard deviation (SD) was used in conjunction with the mean AUC