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

Method : TMlpANN
Creator: cafuser4
Date   : Thu Feb  1 04:10:12 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_5709/work/macros3
Training events: 79180


#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'    [20.134,501.348]
                        LepBEn                        LepBEn    'F'    [10.0054,469.956]
                       dilmass                       dilmass    'F'    [16.0001,749.693]
                        metmag                        metmag    'F'    [0.0479105,310.187]
                         addEt                         addEt    'F'    [33.7775,808.484]
                     dPhiMetLJ                     dPhiMetLJ    'F'    [2.03754e-05,3.13922]
                    ntightjets                    ntightjets    'F'    [0,3]
                       jet1_Et                       jet1_Et    'F'    [0,73.6943]
                       jet2_Et                       jet2_Et    'F'    [0,43.0122]
                       dildphi                       dildphi    'F'    [5.1112e-05,3.14158]
                          lepR                          lepR    'F'    [0.350159,4.18507]
                        metsig                        metsig    'F'    [0.00413108,15.8344]


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

#input normalization
27.7592 78.4629
18.6108 37.1626
35.7598 86.7207
16.6073 45.792
30.2082 136.038
0.770013 1.19356
0.404768 0.147843
9.89444 3.54513
2.84092 0.381715
0.822869 2.23201
0.768688 2.47856
1.44987 3.81168
#output normalization
1 0
#neurons weights
-0.0873036
-0.173436
-0.235688
0.11949
-0.178475
0.195141
-0.23727
0.0678002
0.31274
-0.115626
-0.232152
-0.487193
-2.21829
2.09374
0.374449
0.803811
-0.00736838
-0.111985
0.000480663
-0.793063
0.204586
-0.11122
0.767437
-0.361133
-3.1376
0.304804
-0.635867
-0.215154
-0.532796
0.72453
0.15631
0.441054
0.381425
-0.628792
-1.35283
-0.136393
0.146426
-0.00598181
#synapses weights
0.175052
-0.0788572
1.13465
-2.76021
-0.0612517
0.0356657
-0.0237331
-0.0242423
0.0240414
1.23665
-0.815824
2.93631
-0.0326263
1.20788
-0.770975
0.595536
-3.40057
1.2913
0.733391
0.132067
-0.0994391
0.712623
-1.88426
-0.782677
-1.19765
2.38637
0.770902
-0.857527
-0.905063
0.539459
0.288437
0.277146
-0.0312374
-1.42327
-0.273167
0.965483
-0.709628
0.346856
-0.584031
-0.638864
-1.10582
0.309575
0.585816
0.202416
-0.0661211
0.864695
-0.833973
0.159604
-0.262685
0.233054
-0.226744
1.07834
-1.01974
-0.213916
0.131618
0.120938
0.169289
-0.240167
0.643496
0.525284
-0.836646
0.0273502
-0.24151
0.736735
-1.00112
-0.252625
-0.0287307
0.286471
-0.647594
-0.082913
-0.122369
0.531574
0.144874
-0.42305
-0.833647
-1.13764
-1.37209
0.725593
0.145465
-0.00594045
0.218937
-0.00367077
-0.600449
-0.920554
0.514304
-0.547441
-0.463277
-0.204847
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0.461874
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0.32057
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0.154409
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0.30902
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0.819375
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0.185643
0.808615
0.774657
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-0.741499
0.441246
0.112731
0.679151
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-0.336364
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0.755121
0.719299
0.295836
-0.152863
0.24249
0.333017
-1.22135
0.518669
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-0.0242
0.387339
0.0115596
0.00707459
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1.96177
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1.30574
1.08799
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0.0791549
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0.374604
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-1.32601
0.0842131
0.0968622
3.1523
0.723681
0.412896
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0.0178883
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0.126333
0.363036
0.302801
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0.061807
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0.169656
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1.01908
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0.441667
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0.0789689
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0.00897058
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0.953863
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0.557334
0.700232
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0.151221
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0.0713284
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0.0371636
0.412065
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0.220834
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0.807174
0.69045
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1.05807
1.34088
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0.71772
0.0789595
-1.5278
-2.02789
0.129418
0.724434
0.52763
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0.458075
-0.354729
0.437812
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-0.636729
0.389105
0.267686
-0.0397158
0.222001
0.342911
0.242545
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0.00796448
0.357144
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0.73034
0.671675
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-1.0069
0.774786
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0.901953
1.92626
-0.901682
-0.124263