...
- divide into 4 jet / 6 jet topologies
- apply preselection depending on topology
- train/apply TMVA's
- validate with cut table
- check remaining backgrounds
^variables_id_c1.png|||||\ ^variables_id_c2.png|||||\ ^variables_id_c3.png|||||\
...
Preselection variables:
| Code Block |
|---|
Evis<140.0: (4 Jet category) # nTrks>10 && # EvisJETS>60.0 && # PTvisJETS>5.0 && # hmass>50. && hmass<140. && # fabs(fabs(dph)-3.14159)>0.15 && # ej1>40. && # jetthrust<0.99 Evis>140: (6 jet category) # nTrks>20 && # EvisJETS<220.0 && # PTvisJETS>5.0 && # hmass>100. && hmass<150. && # fabs(fabs(dph)-3.14159)>0.05 && # ej1<130. && # jetthrust<0.99 |
...
^variables_id_c1-nopresel.png|||||\ ^variables_id_c2-nopresel.png|||||\ ^variables_id_c3-nopresel.png|||||\
nu nu H only:
^variables_id_c1-4jonly.png|||||\ 
| Code Block |
|---|
--- Classifier ( #signal, #backgr.) Optimal-cut S/sqrt(S+B) NSig NBkg EffSig EffBkg --- -------------------------------------------------------------------------------------------------- --- Cuts: (172.67554, 53762.5) 0.0350 2.42407 5.876106 0 0.03403 0 --- Likelihood: (172.67554, 53762.5) 0.7786 0.910341 161.7188 31396.51 0.9365 0.584 --- Fisher: (172.67554, 53762.5) 0.0942 5.84493 34.16319 0 0.1978 0 --- BDTG: (172.67554, 53762.5) 0.4529 4.48342 20.10101 0 0.1164 0 --- BDT: (172.67554, 53762.5) 0.1717 5.33182 28.42833 0 0.1646 0 --- -------------------------------------------------------------------------------------------------- |
...
| Code Block |
|---|
--- Classifier ( #signal, #backgr.) Optimal-cut S/sqrt(S+B) NSig NBkg EffSig EffBkg
--- --------------------------------------------------------------------------------------------------
--- Cuts: (491.39883, 1258440) -0.0050 0 0 0 0 0
--- Likelihood: (491.39883, 1258440) 1.0000 0.575508 479.389 693382.9 0.9756 0.551
--- Fisher: (491.39883, 1258440) 0.0274 1.59132 2.532298 0 0.005153 0
--- BDTG: (491.39883, 1258440) -0.9906 0.918097 174.4497 35930.22 0.355 0.02855
--- BDT: (491.39883, 1258440) 0.0076 2.53129 6.407406 0 0.01304 0
--- --------------------------------------------------------------------------------------------------
|
Background contributions for Evis<140:
| Code Block |
|---|
[neal@localhost weights]$ sed 's/\./,/g' zzhpassing.dat | awk '{if ($18<140. && NF==18) print $3,$7,$15}' | sort -n | uniq -c | awk '{if (NF==4) aa+=($1*$4);print $1*$4"\t"$0} END{print "Sum of weights = "aa}' | sort -k 1,1 -n Sum of weights = 575 12,5 1 106551 4f_ww 12,500000 12,5 1 106562 4f_sz 12,500000 12,5 1 106566 4f_sw 12,500000 12,5 1 106572 4f_sz 12,500000 12,5 1 106575 4f_zz 12,500000 12,5 1 106607 2f_z_ 12,500000 25 2 106571 4f_sz 12,500000 37,5 3 106578 4f_ww 12,500000 75 6 106608 2f_z_ 12,500000 137,5 11 106576 4f_zz 12,500000 225 18 106577 4f_ww 12,500000 |
Background contributions for Evis>140:
| Code Block |
|---|
[neal@localhost weights]$ sed 's/\./,/g' zzhpassing.dat | awk '{if ($18>=140. && NF==18) print $3,$7,$15}' | sort -n | uniq -c | awk '{if (NF==4) aa+=($1*$4);print $1*$4"\t"$0} END{print "Sum of weights = "aa}' | sort -k 1,1 -n Sum of weights = 187,5 12,5 1 106551 4f_ww 12,500000 12,5 1 106577 4f_ww 12,500000 25 2 106553 4f_zz 12,500000 25 2 106573 4f_zz 12,500000 25 2 106576 4f_zz 12,500000 37,5 3 106574 4f_zz 12,500000 50 4 106608 2f_z_ 12,500000 |