the open issue on post-processing / prior adjustment to adjust for
class_weight: https://github.com/scikit-learn/scikit-learn/issues/10613
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We don't usually do any postprocessing for class weight (although there is
an open issue:).
In the second taxonomy, I'd say Data Pre-processing ("weighting the data
space"), but maybe there are exceptions in some estimators.
The classification in the first taxonomy is correct, IMO.
In the third,
Hi
Thanks a lot for your time and consideration. I have seen imblearn but my
question is not related to it.
Best regards,
On Tue, Jun 19, 2018 at 9:04 PM, Christos Aridas wrote:
> Hi,
>
> Have you seen http://imbalanced-learn.org?
>
> Best,
> Chris
>
> On Tue, 19 Jun 2018 17:53 S Hamidizade,
Hi,
Have you seen http://imbalanced-learn.org?
Best,
Chris
On Tue, 19 Jun 2018 17:53 S Hamidizade, wrote:
> Hi
>
> I would appreciate if you could let me know what is the best way to
> categorize the approaches which have been developed to deal with imbalance
> class problem?
>
> *This article
