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Hi, thanks for your code and dataset, it really helps me a lot; however, I have been confused about the way
you calculate the sensitivity and specificity while calculating remission.
You regard nonremission as positive here:
"util.py/provider.py", line 723:
r_probs.append(output.softmax(1).squeeze(0)[nonremission_scores].sum().item()) --> you use the nonremission label([2,3]) total probability as the probability of r_probs, it shows that nonremission is positive. And 0 represents remission, 1 represents nonremission here.
You regard nonremission as negative here:
"train_classification_model_CV.py", line 383:
cr_r = classification_report(r_true, r_pred, output_dict=True)
sensitivities_r.append(cr_r["0"]["recall"]), specificities_r.append(cr_r["1"]["recall"]) --> it shows that nonremission(1) is negative here.
Q: Is nonremission positive or negative?
Thanks in advance! (really thanks for your contribution to this study!)
Ludwig
The text was updated successfully, but these errors were encountered:
Hi, thanks for your code and dataset, it really helps me a lot; however, I have been confused about the way
you calculate the sensitivity and specificity while calculating remission.
You regard nonremission as positive here:
"util.py/provider.py", line 723:
r_probs.append(output.softmax(1).squeeze(0)[nonremission_scores].sum().item()) --> you use the nonremission label([2,3]) total probability as the probability of r_probs, it shows that nonremission is positive. And 0 represents remission, 1 represents nonremission here.
You regard nonremission as negative here:
"train_classification_model_CV.py", line 383:
cr_r = classification_report(r_true, r_pred, output_dict=True)
sensitivities_r.append(cr_r["0"]["recall"]), specificities_r.append(cr_r["1"]["recall"]) --> it shows that nonremission(1) is negative here.
Q: Is nonremission positive or negative?
Thanks in advance! (really thanks for your contribution to this study!)
Ludwig
The text was updated successfully, but these errors were encountered: