Yes, but oversampling and calibration is more reasonable approach.
https://research.fb.com/publications/practical-lessons-from-predicting-clicks-on-ads-at-facebook/
> for linear models (such as linear SVM or logistic regression), the class
> weights will alter the loss function by weighting
But class weighting doesnt need recalibration, isnt?
Shadi
On Friday, November 1, 2019, Makoto Yui wrote:
> True. And, I think oversampling is better than class weighting for
> accuracy.
>
> Makoto
>
> 2019年11月1日(金) 19:37 Shadi Mari :
>
>> Thanks for the explanation Makoto.
>>
>> Class weight
True. And, I think oversampling is better than class weighting for accuracy.
Makoto
2019年11月1日(金) 19:37 Shadi Mari :
> Thanks for the explanation Makoto.
>
> Class weight option much like what scikit provides is what am referring
> to; seems its not yet implemented and thus “random”
