#GEN -*-*-*-*-*-*-*-*-*-*-*- general info -*-*-*-*-*-*-*-*-*-*-*-

Method : TMlpANN
Creator: cafuser4
Date   : Thu Feb  1 03:31:22 2007
Host   : Linux patlx3.fnal.gov 2.4.21-37.ELsmp #1 SMP Wed Sep 28 12:13:44 CDT 2005 i686 i686 i386 GNU/Linux
Dir    : /fbsng/condor_local/execute/dir_29455/work/macros3
Training events: 16514


#OPT -*-*-*-*-*-*-*-*-*-*-*-*- options -*-*-*-*-*-*-*-*-*-*-*-*-

# Set by User:
V: False [verbose flag]
NCycles: 200 [Number of training cycles]
HiddenLayers: "N+1,N" [Specification of the hidden layers]
# Default:
D: False [use-decorrelated-variables flag (for backward compatibility, please switch to Preprocess)]
Preprocess: "None" [Variable Decorrelation Method]
PreprocessType: "Signal" [Use signal or background for Preprocess]
H: False [help flag]
##


#VAR -*-*-*-*-*-*-*-*-*-*-*-* variables *-*-*-*-*-*-*-*-*-*-*-*-

NVar 12
                        LepAEn                        LepAEn    'F'    [20.1975,308.823]
                        LepBEn                        LepBEn    'F'    [10.0538,386.004]
                       dilmass                       dilmass    'F'    [16.0014,567.836]
                        metmag                        metmag    'F'    [0.0417844,179.809]
                         addEt                         addEt    'F'    [34.3796,562.99]
                     dPhiMetLJ                     dPhiMetLJ    'F'    [0.000296664,3.13571]
                    ntightjets                    ntightjets    'F'    [0,5]
                       jet1_Et                       jet1_Et    'F'    [0,298.338]
                       jet2_Et                       jet2_Et    'F'    [0,141.192]
                       dildphi                       dildphi    'F'    [0.000116093,3.14158]
                          lepR                          lepR    'F'    [0.401325,3.64288]
                        metsig                        metsig    'F'    [0.00334611,10.4178]


#WGT -*-*-*-*-*-*-*-*-*-*-*-*- weights -*-*-*-*-*-*-*-*-*-*-*-*-

#input normalization
10.3391 48.9992
9.70371 41.035
24.5032 79.2858
21.5613 16.2677
19.0779 99.9309
0.839944 0.661229
0.52853 0.204766
18.1922 6.15693
5.70956 1.01369
0.874888 2.62935
0.803404 2.71506
1.83089 1.40178
#output normalization
1 0
#neurons weights
-0.263221
0.394365
-0.151402
-0.0383869
-0.449708
-0.199165
0.48882
-0.386866
0.359359
0.16278
0.00209599
0.171354
0.230645
-0.668552
0.531873
-1.67597
-0.649132
0.460226
0.210501
-0.141784
-1.91841
-0.195427
-0.145977
-0.0152305
-0.656661
0.140916
-0.0208812
-0.657486
0.69845
-0.0302585
0.651522
0.425066
0.294772
-0.157649
0.214533
-0.546628
-0.183809
-0.153043
#synapses weights
-1.38674
1.17546
-0.840463
1.21583
0.524122
-0.607847
-0.899656
0.49172
0.996433
-0.87623
-1.15448
4.40543
-0.282864
-0.115344
-1.27213
1.64665
0.489552
0.422686
0.164887
0.981728
1.26747
-0.379571
1.10828
-1.0728
-1.02554
1.30056
1.16264
-1.37195
-1.94583
-0.0529687
-0.26296
0.00817873
-0.470066
0.439952
0.46892
-2.44211
0.0664196
0.320595
0.385417
0.296717
-0.546722
-0.349146
0.317664
0.861426
-0.566462
0.447326
1.37048
-3.08707
-0.127121
-0.678157
-0.159028
0.956913
-0.020783
-1.23594
-0.741028
-0.208143
0.606013
-0.751933
-0.108086
-0.252201
0.815733
0.508154
1.32797
-2.91204
-1.26594
-0.518241
0.378874
-1.08352
-0.544248
0.453471
0.595306
-1.24517
-0.421191
-0.385825
-0.101833
-0.0582913
0.427771
0.878756
-0.008426
-0.170767
-0.619249
-1.00755
-0.467141
0.851948
-0.525816
-0.529253
-0.586242
1.22178
0.976355
0.38568
-0.600807
0.154139
-0.0307447
-0.0821498
-0.0998766
0.128668
-0.113083
-0.133524
2.07597
-2.31925
-1.78942
-0.925354
0.996511
0.256339
-0.552951
0.163497
-0.0777644
-4.56009
0.469671
-0.133389
-5.44741
0.573385
-1.15886
0.297143
-0.231155
0.32724
0.211535
0.0509078
-1.32973
1.86136
-0.318417
-0.029033
0.924052
-0.394427
-0.283388
-0.460209
0.490047
0.0185101
-0.238484
1.17406
0.733915
0.466232
0.303228
0.682572
0.0718188
0.335213
-0.865791
-0.0209459
0.115388
-1.04714
-0.297232
-0.231422
0.0780232
-2.46686
-0.239087
1.18108
0.665257
-0.503951
0.394536
0.769541
-0.531547
-0.307789
0.212102
-0.558821
0.0893545
-1.54499
-0.185338
0.0726468
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0.0193106
-0.223989
0.0269511
0.389308
0.47859
0.247302
0.378322
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0.266774
1.32501
-0.167453
-1.01686
-1.27803
0.730241
0.226102
-0.00300094
0.3708
-1.30714
1.5555
-0.384417
-0.410431
-0.612458
-0.649545
-0.0849782
-0.112413
-0.325273
-0.414933
-0.322643
-0.149171
-0.269922
-0.358926
0.186247
-0.410451
-0.271342
-0.0846247
2.99419
-2.48249
-1.77918
-2.3254
-1.24369
1.88674
0.770565
-0.491347
-2.15923
3.71757
1.40412
-2.6537
-1.53597
0.307213
0.194603
0.184214
0.0623711
-0.381977
-0.0623837
0.324873
-0.337459
-0.140966
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-0.224726
-0.130367
-0.213936
0.281843
0.0239682
-0.0564619
-0.0667613
0.3335
0.146245
0.0682909
-0.190804
-0.109616
0.620346
0.256533
0.000358602
-0.663745
0.0184029
-0.058386
0.0290307
-0.437474
0.400295
-0.313519
-0.0920587
0.180236
-0.173443
0.316517
0.220557
-0.0820794
0.0735038
0.204475
0.208045
-0.348631
0.0865737
-0.479695
-0.250963
-0.372657
0.526016
-0.404008
0.490895
-0.413404
-0.0791222
-0.476202
0.213951
-0.402491
0.0746451
-0.648905
-0.16394
0.211632
0.128839
-0.701508
-1.05928
0.240019
-0.263683
-0.19355
-0.781723
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0.193887
0.0994747
-0.555815
0.284012
-1.05914
0.00639735
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0.085054
0.0749601
-0.742968
-0.0172232
-0.242983
0.605575
-0.0312778
-0.545463
-0.227667
-0.361648
0.629976
0.0276394
-0.127245
-0.284228
0.406757
-0.087447
-0.155804
-0.291219
-0.294037
0.195691
0.101487
0.141955
0.16858
0.117116
0.193578
-0.0352488
0.68631
-0.718763
-0.230267
0.0329445
0.572004
0.169441
-1.31967
0.429641
1.906
-0.00965199
-0.0736222
0.347454
0.0300854
-0.211541
0.570377
-0.129841
-0.154676