Dear Experts,
I’m using TMVA in order to optimize a selection.
I set the weights for Signal and Backgrounds with:
factory.AddSignalTree ( signal, signalWeight )
factory.AddBackgroundTree( background, backgroundWeight )
Where signalWeight and backgroundWeight are the weight for the S and B, given by the cross section and the number of events generated in the MC.
Then, when I look at the output from TMVAGui.C I see that:
a) All the plots like mva_LikelihoodD.png are normalized to same area (but I know this is normal).
b) The plots like mvaeffs_BDT.png have written a value for S/sqrt(S/B) that is unrealistic, since here the relative normalization has not been taken into account.
The efficiencies for S and B are independent from the relative normalization, but the purity, the signal efficiency*purity and the s/sqrt(S+B) values make no sense without the relative normalization.
So I ask:
- How can I be sure that the normalization has been taken into account?
- How can I have plots where the normalization is taken into account?
Thanks a lot,
Luca