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Data Science

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  • $\begingroup$ I don't have the same output. Mine is 0.9 AUC in both V1 and V2 $\endgroup$ Commented Aug 19 at 16:17
  • $\begingroup$ @underflow please can you provide the complete output and I will take a look. $\endgroup$ Commented Aug 19 at 18:31
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    $\begingroup$ @robert first of all thank you so much for this magnificent explanation ! I feel more confident especially since I was opting for strategy 1 all the way. Now I will investigate other strategies. My question is, when dealing with a supervised learning use cases can we limit the process to model performance monitoring (AUC, ROC, FPR, F1-score, Accuracy) and ignore the statistical metrics and statistical tests? $\endgroup$ Commented Aug 25 at 12:55
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    $\begingroup$ @RobertLong Sorry for the delay and sorry it was my mistake - the code works well. $\endgroup$ Commented Aug 30 at 12:10