I have done a 10-fold cross validation and I have a list of 10 including sensitivity, specificity, threshold, AUC,... I would like to make a final roc curve plot as an average roc from this list. Also, to know what is the optimal cutoff (top left corner), sensitivity and specificity. Anyone can help of this?
Can I take the mean of sensitivity, specificity, ... of each 10 list? if yes, how? thanks
thanks. I would like to add some information to get further help.
1)My original cutoff, specificity and sensitivity are:
2) from 10-fold cross-validation:
3) after taking mean:
These does make sense? or wrong?
I have no idea what cutoff is in this context, nor what you mean by
I don't know how you got those values for means. I get 0.8831 for cutoff, 0.7726 for specificity and 0.7445 for sensitivity. Your mean values seem to repeat what is in the first row.
Either way, calculating this from an out-of-fold sample is the way to go. You are already making predictions for validation data, or else you wouldn't have these calculated values. So just put all validation predictions together into one dataframe, and in the end you will have the same size as your train data, but calculated out of fold. Then you can calculate the final values on that complete dataset, without any averaging.
thanks for your help