jmvllt wrote
> Here, because the predicted class will always be 0 or 1, there is no way
> to vary the threshold to get the aucROC, right Or am I totally wrong
> ?
No, you are right. If you pass a (Score,Label) tuple to
BinaryClassificationMetrics, then Score has to be the class probability.
Hi filthysocks,
Thanks for the answer. Indeed, using the clearThreshold() function solved my
problem :).
Regards,
Jean.
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Hi guys,
This may be a stupid question. But I m facing an issue here.
I found the class BinaryClassificationMetrics and I wanted to compute the
aucROC or aucPR of my model.
The thing is that the predict method of a LogisticRegressionModel only
returns the predicted class, and not the
Your reasoning is correct; you need probabilities (or at least some
score) out of the model and not just a 0/1 label in order for a ROC /
PR curve to have meaning.
But you just need to call clearThreshold() on the model to make it
return a probability.
On Tue, Nov 24, 2015 at 5:19 PM, jmvllt
