Timeline for Choosing a Cut-Off Value from an ROC Curve for a Cross Validated Dataset
Current License: CC BY-SA 4.0
4 events
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| Aug 5, 2022 at 13:28 | comment | added | MauM99 | Ah, I see. If you have the time could you also answer the other questions I added to the comment? :) | |
| Aug 5, 2022 at 13:14 | comment | added | cbeleites | @MauM99: yes: you set yourself some rule how to determine the cutoff, but for different folds (and for the combined predictions of all folds) the cutoff predicted probabiliy differs. | |
| Aug 5, 2022 at 13:10 | comment | added | MauM99 | 1. What do you mean by "variation in the cutoffs determined via cross validation"? I would pick the values based on sensitivity and specifity. Do you mean if I get cut-offs that strongly differ despite equal sensitivity and specifity? I got a set of 1000 entries, if that helps. 2. Should I split each fold into trainining, validating (for the AUC) and testing then? 3. What indicators next to AUC would you recommend? Thank you for your answer :) | |
| Aug 5, 2022 at 12:04 | history | answered | cbeleites | CC BY-SA 4.0 |