[TMVA-users] Training a BDT with sweights

[Christophe C. <chr...@tu...>]

Dear experts, 

I'm experiencing some trouble training a BDT with TMVA. 

As far as I can decide the classifier distribution looks not too bad for the BDT
* https://dl.dropbox.com/u/171315/tmva/classifier_distribution_BDT.png
as well as for a Fisher discriminant which I use as a reference, since I was always getting quite good results with it:
* https://dl.dropbox.com/u/171315/tmva/classifier_distribution_Fisher.png

However the the cut efficiencies as well as the ROC curve look very strange:
* https://dl.dropbox.com/u/171315/tmva/cut_efficiencies_BDT.png
* https://dl.dropbox.com/u/171315/tmva/cut_efficiencies_Fisher.png
* https://dl.dropbox.com/u/171315/tmva/ROC_curve.png

I'm using a single TTree as input and sweights from an sSplot via:

factory->SetWeightExpression("sweight_sig", "Signal");
factory->SetWeightExpression("sweight_bkg", "Background");


to discriminate between signal and background events for training and testing.

There are about 130k signal and 20k background events in my sample.

As I never experienced such problems before I guess it has something to do with the sweights.

Do you ever tried that before or have a clue whats going wrong?

Thanks
Christophe



PS:
The TMVA output is:
https://dl.dropbox.com/u/171315/tmva/tmva_output.txt

The factory options are
V:!Silent:Color:DrawProgressBar:Transformations=I;D;P;G,D:AnalysisType=Classification

The split options are:
SplitMode=Random:!V:SplitSeed=0:nTrain_Signal=0:nTest_Signal=0:nTrain_Background=0:nTest_Background=0

The BDT options are:
!V:NTrees=400:nEventsMin=400:MaxDepth=3:BoostType=AdaBoost:SeparationType=GiniIndex:nCuts=20:PruneMethod=NoPruning:VarTransform=Decorrelate
I also tried adding IgnoreNegWeightsInTraining