Benchmark with independent classification model about hep_ml

[arogozhnikov]

@jalvear2dxc yes, seems to match with what I suggested

[arogozhnikov]

Hi @jalvear2dxc,
I'm not completely following which classifiers you compare, but large difference you report is possible.

Naturally, reweighing would remove discrepancies that are picked by models with tree configuration (e.g. depth) that is similar to reweighter's trees.
If you use uniforming loss, this may become an additional hint to classifier (though hard to predict without understanding/pondering the data).

Also, check that you use correct weights in every training and in every AUC scoring. Just in case.

[jalvear2dxc]

Thanks Mr. @arogozhnikov.

I've improved dramatically the results not training a new classifier after the reweighting but just correcting the predictions of the firs model with the predicted weigths. Does it make sense? I think this is according with what you said in the answer.