I am very interested in your paper. But when it comes to accuracy assessment, I have some problems. You used "prfs(labels.data.cpu().numpy().flatten(), cd_preds.data.cpu().numpy().flatten(), average='binary', pos_label=1 in train )" for accuracy evaluation, and use "tn, fp, fn, tp =
confusion_matrix(labels.data.cpu().numpy().flatten(),cd_preds.data.cpu().numpy().flatten()).ravel()" in eval. During the calculation, I found that the accuracy of the two methods differed by up to 10%. May I ask why the accuracy of the two methods is so different. Which method is more reliable for accuracy assessment?
Looking forward to your answer, thank you!
I am very interested in your paper. But when it comes to accuracy assessment, I have some problems. You used "prfs(labels.data.cpu().numpy().flatten(), cd_preds.data.cpu().numpy().flatten(), average='binary', pos_label=1 in train )" for accuracy evaluation, and use "tn, fp, fn, tp = confusion_matrix(labels.data.cpu().numpy().flatten(),cd_preds.data.cpu().numpy().flatten()).ravel()" in eval. During the calculation, I found that the accuracy of the two methods differed by up to 10%. May I ask why the accuracy of the two methods is so different. Which method is more reliable for accuracy assessment? Looking forward to your answer, thank you!