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pT m max. pT m min. Df ll. MET. M ll. USUAL VARIABLES. Distributions before Jet veto. H160 WW ttbar. h m max. h m min. DphimuMetmax. DphimuMetmin. MTmax. MTmin. SumET. NEW VARIABLES. Ntracks. H160 WW ttbar.
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pTm max pTm min Dfll MET Mll USUAL VARIABLES Distributions before Jet veto H160 WW ttbar hm max hm min
DphimuMetmax DphimuMetmin MTmax MTmin SumET NEW VARIABLES Ntracks H160 WW ttbar
Starting point Skimming + preselection + HLT +muon selection TRAINING 160
1. Training against WW Preselection: --- DataSet : On signal input : MET>30 && InvMass>12 --- DataSet : On background input : MET>30 && InvMass>12 • Training signal entries : 7200 • Training background entries : 7200 ---------------------------------------------------------------- BDT : Ranking result (top variable isbestranked) ---------------------------------------------------------------- Rank : Variable : Variable Importance ---------------------------------------------------------------- 1 : Dphill : 2.819e-01 2 : Mtmin : 1.573e-01 3 : etalepmin : 8.728e-02 4 : MET : 7.767e-02 5 : etalepmax : 6.933e-02 6 : InvMass : 6.621e-02 7 : ptlepmin : 4.916e-02 8 : DphiLepMetmin : 4.636e-02 9 : SumEt : 4.154e-02 10 : DphiLepMetmax : 3.520e-02 11 : Mtmax : 3.438e-02 12 : Ntracks : 3.290e-02 13 : ptlepmax : 2.069e-02 ---------------------------------------------------------------- BDT parameters Ncuts = 20 #Trees=1000 Pruning = 10.5
Evaluation results ranked by best signal efficiency and purity (area) ----------------------------------------------------------------------------- MVA Signal efficiency at bkg eff. (error): | Sepa- Signifi- Methods: @B=0.01 @B=0.10 @B=0.30 Area | ration: cance: ----------------------------------------------------------------------------- MLP : 0.125(10) 0.727(14) 0.932(07) 0.911 | 0.544 1.470 BDT : 0.155(11) 0.711(14) 0.912(08) 0.906 | 0.533 1.425 ----------------------------------------------------------------------------- Testing efficiency compared to training efficiency (overtraining check) ----------------------------------------------------------------------------- MVA Signal efficiency: from test sample (from traing sample) Methods: @B=0.01 @B=0.10 @B=0.30 ----------------------------------------------------------------------------- MLP : 0.125 (0.276) 0.727 (0.721) 0.932 (0.925) BDT : 0.155 (0.328) 0.711 (0.716) 0.912 (0.923) -----------------------------------------------------------------------------
2. Training against ttbar Preselection: --- DataSet : On signal input : MET>30 && InvMass>12 --- DataSet : On background input : MET>30 && InvMass>12 --- DataSet : - Training signal entries : 13496 --- DataSet : - Training background entries : 14800 (test tmva - 167 samples) Factory : Evaluation results ranked by best signal efficiency and purity (area) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency at bkg eff. (error): | Sepa- Signifi- --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 Area | ration: cance: --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.540(08) 0.878(05) 0.973(02) 0.958 | 0.684 2.007 --- Factory : ----------------------------------------------------------------------------- --- Factory : --- Factory : Testing efficiency compared to training efficiency (overtraining check) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency: from test sample (from traing sample) --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.540 (0.587) 0.878 (0.892) 0.973 (0.976) --- Factory : -----------------------------------------------------------------------------
BDT parameters Ncuts = 20 #Trees=1000 Pruning = 12.5 R1=sqrt( (0.95-bdt1)^2 + (0.95-bdt2)^2) R2=sqrt( (0.7-bdt1)^2 + (0.9-bdt2)^2)
S/B S/B BDT_1 training against WW BDT_2 training againstttbar Try to find the best cut for each mass MH=140-150 R2=sqrt( (0.7-bdt1)^2 + (0.9-bdt2)^2) MH=160 - 170 R1=sqrt( (0.95-bdt1)^2 + (0.95-bdt2)^2)
SIGNAL 100 pb-1 BACKGROUNDS
1. Training against WW : Preselection: --- DataSet : On signal input : MET>30 && InvMass>12 --- DataSet : On background input : MET>30 && InvMass>12 : Collected: --- DataSet : - Training signal entries : 7200 --- DataSet : - Training background entries : 7200 : ---------------------------------------------------------------- --- BDT : Rank : Variable : Variable Importance --- BDT : ---------------------------------------------------------------- --- BDT : 1 : Dphill : 2.240e-01 --- BDT : 2 : InvMass : 1.985e-01 --- BDT : 3 : etalepmin : 1.077e-01 --- BDT : 4 : etalepmax : 1.069e-01 --- BDT : 5 : DphiLepMetmin : 5.870e-02 --- BDT : 6 : MET : 4.453e-02 --- BDT : 7 : Mtmax : 4.414e-02 --- BDT : 8 : Mtmin : 4.098e-02 --- BDT : 9 : DphiLepMetmax : 3.909e-02 --- BDT : 10 : Ntracks : 3.726e-02 --- BDT : 11 : SumEt : 3.388e-02 --- BDT : 12 : ptlepmax : 3.232e-02 --- BDT : 13 : ptlepmin : 3.200e-02 --- BDT : ------------------------------------------------------- BDT parameters Ncuts = 30 #Trees=1000 Pruning = 16.5
Evaluation results ranked by best signal efficiency and purity (area) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency at bkg eff. (error): | Sepa- Signifi- --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 Area | ration: cance: --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.135(10) 0.555(15) 0.882(10) 0.873 | 0.477 1.248 --- Factory : ----------------------------------------------------------------------------- --- Factory : --- Factory : Testing efficiency compared to training efficiency (overtraining check) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency: from test sample (from traing sample) --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.135 (0.223) 0.555 (0.648) 0.882 (0.923) --- Factory : -----------------------------------------------------------------------------
1. Training againstttbar : Preselection: --- DataSet : On signal input : MET>30 && InvMass>12 --- DataSet : On background input : MET>30 && InvMass>12 : - Training signal entries : 7200 --- DataSet : - Training background entries : 9200 - BDT : Ranking result (top variable is best ranked) --- BDT : ---------------------------------------------------------------- --- BDT : Rank : Variable : Variable Importance --- BDT : ---------------------------------------------------------------- --- BDT : 1 : Ntracks : 2.549e-01 --- BDT : 2 : SumEt : 1.703e-01 --- BDT : 3 : InvMass : 1.019e-01 --- BDT : 4 : DphiLepMetmax : 8.459e-02 --- BDT : 5 : Dphill : 7.530e-02 --- BDT : 6 : etalepmax : 6.814e-02 --- BDT : 7 : etalepmin : 4.648e-02 --- BDT : 8 : DphiLepMetmin : 4.357e-02 --- BDT : 9 : Mtmin : 4.069e-02 --- BDT : 10 : MET : 3.565e-02 --- BDT : 11 : Mtmax : 3.366e-02 --- BDT : 12 : ptlepmin : 2.300e-02 --- BDT : 13 : ptlepmax : 2.183e-02 --- BDT : ---------------------------------------------------------------- BDT parameters Ncuts = 20 #Trees=1000 Pruning = 12.5
--- Factory : Evaluation results ranked by best signal efficiency and purity (area) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency at bkg eff. (error): | Sepa- Signifi- --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 Area | ration: cance: --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.515(15) 0.884(10) 0.983(04) 0.963 | 0.720 2.051 --- Factory : ----------------------------------------------------------------------------- --- Factory : --- Factory : Testing efficiency compared to training efficiency (overtraining check) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency: from test sample (from traing sample) --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.515 (0.615) 0.884 (0.895) 0.983 (0.984) --- Factory : -----------------------------------------------------------------------------
H130 WW ttbar Z+jets W+jets BDT 2D
S/B MH=120 - 140 R=sqrt( (0.95-bdt1)^2 + (0.95-bdt2)^2)
SIGNAL BACKGROUNDS
1. Training against WW : Preselection: --- DataSet : On signal input : MET>30 && InvMass>12 --- DataSet : On background input : MET>30 && InvMass>12 --- DataSet : - Training signal entries : 7200 --- DataSet : - Training background entries : 7200 --- BDT : Ranking result (top variable is best ranked) --- BDT : ---------------------------------------------------------------- --- BDT : Rank : Variable : Variable Importance --- BDT : ---------------------------------------------------------------- --- BDT : 1 : Dphill : 1.898e-01 --- BDT : 2 : MET : 1.231e-01 --- BDT : 3 : Mtmin : 1.201e-01 --- BDT : 4 : InvMass : 9.526e-02 --- BDT : 5 : etalepmax : 8.677e-02 --- BDT : 6 : SumEt : 7.795e-02 --- BDT : 7 : etalepmin : 6.269e-02 --- BDT : 8 : Ntracks : 4.665e-02 --- BDT : 9 : ptlepmax : 4.494e-02 --- BDT : 10 : Mtmax : 4.291e-02 --- BDT : 11 : DphiLepMetmin : 4.228e-02 --- BDT : 12 : DphiLepMetmax : 3.788e-02 --- BDT : 13 : ptlepmin : 2.964e-02 --- BDT : ---------------------------------------------------------------- BDT parameters Ncuts = 30 #Trees=400 Pruning = 12.5
--- Factory : Evaluation results ranked by best signal efficiency and purity (area) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency at bkg eff. (error): | Sepa- Signifi- --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 Area | ration: cance: --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.245(13) 0.643(15) 0.850(11) 0.871 | 0.457 1.182 --- Factory : ----------------------------------------------------------------------------- --- Factory : --- Factory : Testing efficiency compared to training efficiency (overtraining check) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency: from test sample (from traing sample) --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.245 (0.286) 0.643 (0.592) 0.850 (0.834) --- Factory : -----------------------------------------------------------------------------
1. Training againstttbar : Preselection: --- DataSet : On signal input : MET>30 && InvMass>12 --- DataSet : On background input : MET>30 && InvMass>12 --- DataSet : - Training signal entries : 8000 --- DataSet : - Training background entries : 10000 --- BDT : Ranking result (top variable is best ranked) --- BDT : ---------------------------------------------------------------- --- BDT : Rank : Variable : Variable Importance --- BDT : ---------------------------------------------------------------- --- BDT : 1 : Ntracks : 3.699e-01 --- BDT : 2 : SumEt : 2.481e-01 --- BDT : 3 : Mtmin : 4.972e-02 --- BDT : 4 : Dphill : 4.835e-02 --- BDT : 5 : InvMass : 4.676e-02 --- BDT : 6 : etalepmax : 4.118e-02 --- BDT : 7 : DphiLepMetmax : 3.956e-02 --- BDT : 8 : DphiLepMetmin : 3.205e-02 --- BDT : 9 : etalepmin : 2.947e-02 --- BDT : 10 : ptlepmin : 2.601e-02 --- BDT : 11 : MET : 2.485e-02 --- BDT : 12 : ptlepmax : 2.246e-02 --- BDT : 13 : Mtmax : 2.168e-02 --- BDT : ---------------------------------------------------------------- BDT parameters Ncuts = 20 #Trees=1000 Pruning = 11.5
--- Factory : Evaluation results ranked by best signal efficiency and purity (area) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency at bkg eff. (error): | Sepa- Signifi- --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 Area | ration: cance: --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.340(14) 0.749(13) 0.903(09) 0.907 | 0.541 1.401 --- Factory : ----------------------------------------------------------------------------- --- Factory : --- Factory : Testing efficiency compared to training efficiency (overtraining check) --- Factory : ----------------------------------------------------------------------------- --- Factory : MVA Signal efficiency: from test sample (from traing sample) --- Factory : Methods: @B=0.01 @B=0.10 @B=0.30 --- Factory : ----------------------------------------------------------------------------- --- Factory : BDT : 0.340 (0.407) 0.749 (0.753) 0.903 (0.905) --- Factory : ----------------------------------------------------------------------------
WW H130 ttbar Z + jets W+jets
S/B S/B R2=sqrt( (0.95-bdt1)^2 + (0.95-bdt2)^2) MH=190- 200 MH=180 R1=sqrt( (0.75-bdt1)^2 + (0.9-bdt2)^2)
SIGNAL BACKGROUNDS
Significance BDT Cut-based mass dependent 100 pb-1
Significance BDT Cut-based mass dependent 1 fb-1