evaluate the performance of the classification model50. The ROC is a probability curve that shows the trade-off between the true positive rate (TPR) and false-positive rate (FPR) using different threshold settings. The AUROC provides a measure of separability and demonstrated the discriminative capacity of the classification model. The larger the AUROC, the better the performance of the model is for predicting the true positive