Fig. 3
Local vs. distant recurrence results on the validation set. (A) shows slight differences in training and testing accuracies of 6 machine learning models. (B) reveals the performance of the evaluation metrics: Accuracy, Recall, and F1 score. (C) combines the confusion matrices of all 6 models. The confusion matrix displays the predicted classes on the X-axis and the true classes on the Y-axis, with the color of the diagonal blocks illustrating the closeness of the match between the predicted and true class. The darker the blue color of the diagonal line, the better the model prediction accuracy. (D) is a combined ROC curve for all 6 models.
