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Use AUC to evaluate multiclass problems
Рет қаралды 8,485
Күн бұрынAUC is an excellent evaluation metric for binary classification, especially if you have class imbalance.
New in scikit-learn 0.22: AUC can be used with multiclass problems! Supports "one-vs-one" and "one-vs-rest" strategies.
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@dataschool 3 жыл бұрын
New to ROC curves and AUC? Check out my 14-minute explanation: kzfaq.info/get/bejne/haecachy3raRqaM.html (it's my 2nd most popular video!)
@cgmiguel 2 жыл бұрын
It would be nice to hear about your thoughts on AUC ROC vs AUC PR, for imbalanced sets (or any other metic for that matter). Thanks for sharing!
@dataschool 2 жыл бұрын
Great question! I've got a long lesson about that topic in my upcoming ML course, but unfortunately I can't boil it down to a few sentences. Stay tuned!
@felixisnr1 3 жыл бұрын
thank you for all your vids, really appreciated. do you plan to do a short series for plotting? would love to see this on your channel if you find the time to do so at one point. either way, thanks a lot. you are such a great teacher!
@dataschool 3 жыл бұрын
Thanks for your suggestion, and for your kind words! I don't have a series on plotting planned, but I'll certainly consider it for the future!
@priyabrataray8663 3 жыл бұрын
Really Helpful 🙂.Can you please suggest a demo dataset for multi class classification
@dataschool 3 жыл бұрын
Glad it's helpful! You could try the iris, digits, or wine datasets: scikit-learn.org/stable/datasets/toy_dataset.html
@beautyisinmind2163 2 жыл бұрын
So how to decide which one should i use actually ovo or ovr if i have 4 classes to be classified
@debabratasikder9448 11 ай бұрын
axis 1 is out of bounds for array of dimension 1
@svitirur1665 3 жыл бұрын
nice, good explanation . I have question can we do binomial /poisson test experiment on a dataset?
@dataschool 3 жыл бұрын
You should be able to do it using SciPy. Hope that helps!
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