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Search options not deleted user 111822

This tag is meant to be used for questions related to how to evaluate a model performance, not only based on standard metrics, but also in the context of real use case applications. What is a good model might depend on many factors to take into account, to eventually get really useful data science applications.

4 votes
1 answer
2k views

Choose ROC/AUC vs. precision/recall curve?

I am trying to get a clear understanding on various classification metrics, including knowing when to choose ROC/AUC as opposed to opting for the Precision/Recall curve. I am reading Aurélien Géron's …
lazarea's user avatar
  • 299
3 votes
2 answers
2k views

Uncertainty about shape of ROC curve

I am working on a binary classification and the plotted ROC curves that I am using for evaluation together with AUC, have seemed strange to me. Here is an example. I understand that ROC is a visual r …
lazarea's user avatar
  • 299
4 votes

Uncertainty about shape of ROC curve

Oops. I found the reason! The shape of ROC returned by the roc_curve depends on the number of unique values that are input to roc_curve. In my case I was getting only 3 points on the ROC curve. The mi …
lazarea's user avatar
  • 299