*AWKWARD VIDEO MISTAKE* : The two models used for disease detection and hiring at 05:06 should be switched in the ROC plot. Sorry for any confusion this mistake may have caused you when watching this and thanks @benedict6695 for pointing it out!

Highly appreciated🙏

Thanks for the video. Did you end up making a video for ROC in multiclass too?

Can I use a similar approach for multiclass but looking at metric balanced accuracy?

Hi Hope you are doing well! Im still a bit confused. Don't you think that the models for disease detection and hiring are switched? (05:06) We are always assuming that the alternative or the H1 as the condition that we wanna predict. Or in other terms, innocent (H0) until proven guilty (H1). Hence: *Disease detection model* Assumed: H0 = No disease H1 = Disease It's okay to have more False Positive (reject True H0) than False Negative (Accept False H0), Or in other term, It's okay for the model to classify more people having a disease (H1) than to have no disease (H0) since it will be more costly. Thus, having a higher False Positive Rate (FPR) is better in this case. The model should be placed on "Upper Right" instead of "Lower Left" *Hiring model* Assumed: H0 = Do not Hire H1 = Hire It's okay to have more False Negative (Accept False H0) than False Positive (reject True H0), Or in other term, It's okay for the model to classify more "Do not Hire" (H0) than to "Hire" (H1) since Hiring "underperfomed people" will be more costly. Thus, having a higher False Negative Rate is better in this case. The model should be placed "Lower Left" instead of "Upper Right" (Lower Left = Low FPR = Higher False Negative Rate) Thanks in advance! Please correct me if Im wrong :)