NNInput NNInputs_110.root Options for steering Constraint : lep1_E<400&&lep2_E<400&& HiLoSbString : SB SbString : Target WeightString : TrainWeight EqualizeSB : 0 EvaluateVariables : 0 SetNBProcessingDefault : 1 UseNeuroBayes : 1 WeightEvents : 1 NBTreePrepEvPrint : 1 NBTreePrepReportInterval : 10000 NB_Iter : 250 NBZero999Tol : 0.001 **** List Parameters **** Method:H6AONN5MEMLP:MLP : !V:NCycles=250:HiddenLayers=N+1,N Value for FileString Not found Value for RandString Not found Value for DilTypeString Not found Determine File Parameters : Info: No file info in tree NNAna::CopyTree: entries= 16347 file= 0 options= lep1_E<400&&lep2_E<400&& SBRatio= 0 wt= 1 SorB = 2 NNAna::CopyTree: SigChoice: lep1_E<400&&lep2_E<400&&Target==1 BkgChoice: lep1_E<400&&lep2_E<400&&Target==0 Creating Signal tree for file: 0 weight: 1 SBRatio = 0 Using copy string: lep1_E<400&&lep2_E<400&&Target==1 Creating Background tree for file: 0 weight: 1 SBRatio = 0 Using copy string: lep1_E<400&&lep2_E<400&&Target==0 NNAna::CopyTree: nsig = 3516 nbkg = 12831 Bkg Entries: 12831 Sig Entries: 3516 Chosen entries: 3516 Warning: entries low (below 6000) Signal fraction: 1 Background fraction: 0.274024 Signal Tree Copy Condition: Background Tree Copy Condition: Actual Background Entries: 12831 Actual Signal Entries: 3516 Entries to split: 3516 Test with : 1758 Train with : 1758 ********************************************* * This product is licenced for educational * * and scientific use only. Commercial use * * is prohibited ! * ********************************************* Your number of nodes in the input layer is: 14 Your number of nodes in the hidden layer is: 15 Your number of nodes in the output layer is: 1 You want to do classification You want to use the global preprocessing flag 812 You want to use standard regularisation You use entropy as a loss function You want to use the BFGS algorithm You do not want to fix the shape You use 50 % of patterns for training Weight update after 200 events You want to speed up learning by a factor of 1. You want to limit the learning rate to 0.5 You want to run 250 iterations NeuroBayesTeacher::NB_DEF_DEBUG : setting debug level to 0 You are not allowed to change the debug flag. This is only permitted with a developers licence. NBTreeReportInterval = 10000 NBTreePrepEvPrint = 1 Start Set Inidividual Variable Preprocessing Not touching individual preprocessing for Ht ( 0 ) in Neurobayes Not touching individual preprocessing for LepAPt ( 1 ) in Neurobayes Not touching individual preprocessing for LepBPt ( 2 ) in Neurobayes Not touching individual preprocessing for MetSigLeptonsJets ( 3 ) in Neurobayes Not touching individual preprocessing for MetSpec ( 4 ) in Neurobayes Not touching individual preprocessing for SumEtLeptonsJets ( 5 ) in Neurobayes Not touching individual preprocessing for VSumJetLeptonsPt ( 6 ) in Neurobayes Not touching individual preprocessing for addEt ( 7 ) in Neurobayes Not touching individual preprocessing for dPhiLepSumMet ( 8 ) in Neurobayes Not touching individual preprocessing for dPhiLeptons ( 9 ) in Neurobayes Not touching individual preprocessing for dRLeptons ( 10 ) in Neurobayes Not touching individual preprocessing for lep1_E ( 11 ) in Neurobayes Not touching individual preprocessing for lep2_E ( 12 ) in Neurobayes End Set Inidividual Variable Preprocessing Adding variable Ht To Neurobayes Adding variable LepAPt To Neurobayes Adding variable LepBPt To Neurobayes Adding variable MetSigLeptonsJets To Neurobayes Adding variable MetSpec To Neurobayes Adding variable SumEtLeptonsJets To Neurobayes Adding variable VSumJetLeptonsPt To Neurobayes Adding variable addEt To Neurobayes Adding variable dPhiLepSumMet To Neurobayes Adding variable dPhiLeptons To Neurobayes Adding variable dRLeptons To Neurobayes Adding variable lep1_E To Neurobayes Adding variable lep2_E To Neurobayes NNAna::PrepareNBTraining_: Nent= 3516 for Signal Prepared event 0 for Signal with 3516 events ====Entry 0 Variable Ht : 109.201 Variable LepAPt : 34.6264 Variable LepBPt : 21.6663 Variable MetSigLeptonsJets : 3.417 Variable MetSpec : 30.3435 Variable SumEtLeptonsJets : 78.8573 Variable VSumJetLeptonsPt : 45.7021 Variable addEt : 86.6366 Variable dPhiLepSumMet : 2.13277 Variable dPhiLeptons : 0.457932 Variable dRLeptons : 0.516117 Variable lep1_E : 34.6447 Variable lep2_E : 22.126 ===Show Start ======> EVENT:0 DEtaJ1J2 = 0 DEtaJ1Lep1 = 0 DEtaJ1Lep2 = 0 DEtaJ2Lep1 = 0 DEtaJ2Lep2 = 0 DPhiJ1J2 = 0 DPhiJ1Lep1 = 0 DPhiJ1Lep2 = 0 DPhiJ2Lep1 = 0 DPhiJ2Lep2 = 0 DRJ1J2 = 0 DRJ1Lep1 = 0 DRJ1Lep2 = 0 DRJ2Lep1 = 0 DRJ2Lep2 = 0 DeltaRJet12 = 0 File = 2110 Ht = 109.201 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 34.6264 LepAPt = 34.6264 LepBEt = 21.6667 LepBPt = 21.6663 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 30.3435 MetDelPhi = 1.8502 MetSig = 1.83385 MetSigLeptonsJets = 3.417 MetSpec = 30.3435 Mjj = 0 MostCentralJetEta = 2.37706 MtllMet = 87.0495 Njets = 1 SB = 0 SumEt = 273.78 SumEtJets = 0 SumEtLeptonsJets = 78.8573 Target = 1 TrainWeight = 1 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 45.7021 addEt = 86.6366 dPhiLepSumMet = 2.13277 dPhiLeptons = 0.457932 dRLeptons = 0.516117 diltype = 58 dimass = 14.0486 event = 1653 jet1_Et = 22.5647 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 34.6447 lep2_E = 22.126 rand = 0.999742 run = 229664 weight = 4.9468e-07 ===Show End Adding variable Ht To Neurobayes Adding variable LepAPt To Neurobayes Adding variable LepBPt To Neurobayes Adding variable MetSigLeptonsJets To Neurobayes Adding variable MetSpec To Neurobayes Adding variable SumEtLeptonsJets To Neurobayes Adding variable VSumJetLeptonsPt To Neurobayes Adding variable addEt To Neurobayes Adding variable dPhiLepSumMet To Neurobayes Adding variable dPhiLeptons To Neurobayes Adding variable dRLeptons To Neurobayes Adding variable lep1_E To Neurobayes Adding variable lep2_E To Neurobayes NNAna::PrepareNBTraining_: Nent= 12831 for Background Prepared event 0 for Background with 12831 events ====Entry 0 Variable Ht : 61.1273 Variable LepAPt : 22.7899 Variable LepBPt : 11.7315 Variable MetSigLeptonsJets : 4.52817 Variable MetSpec : 26.6052 Variable SumEtLeptonsJets : 34.5213 Variable VSumJetLeptonsPt : 31.9684 Variable addEt : 61.1273 Variable dPhiLepSumMet : 2.92616 Variable dPhiLeptons : 0.819534 Variable dRLeptons : 0.934366 Variable lep1_E : 23.1166 Variable lep2_E : 12.194 ===Show Start ======> EVENT:0 DEtaJ1J2 = 0 DEtaJ1Lep1 = 0 DEtaJ1Lep2 = 0 DEtaJ2Lep1 = 0 DEtaJ2Lep2 = 0 DPhiJ1J2 = 0 DPhiJ1Lep1 = 0 DPhiJ1Lep2 = 0 DPhiJ2Lep1 = 0 DPhiJ2Lep2 = 0 DRJ1J2 = 0 DRJ1Lep1 = 0 DRJ1Lep2 = 0 DRJ2Lep1 = 0 DRJ2Lep2 = 0 DeltaRJet12 = 0 File = 1 Ht = 61.1273 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 22.7899 LepAPt = 22.7899 LepBEt = 11.7322 LepBPt = 11.7315 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 26.6052 MetDelPhi = 2.37814 MetSig = 2.46258 MetSigLeptonsJets = 4.52817 MetSpec = 26.6052 Mjj = 0 MostCentralJetEta = 0 MtllMet = 61.9133 Njets = 0 SB = 0 SumEt = 116.722 SumEtJets = 0 SumEtLeptonsJets = 34.5213 Target = 0 TrainWeight = 1.94954 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 31.9684 addEt = 61.1273 dPhiLepSumMet = 2.92616 dPhiLeptons = 0.819534 dRLeptons = 0.934366 diltype = 54 dimass = 14.9851 event = 1421455 jet1_Et = 0 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 23.1166 lep2_E = 12.194 rand = 0.999742 run = 271216 weight = 0.0400324 ===Show End Prepared event 10000 for Background with 12831 events Warning: found 410 negative weights. << hh tt >> << hh ii tt >> << hh tttttt >> << ppppp hhhhhh ii tt >> << pp pp hhh hh ii ----- tt >> << pp pp hh hh ii ----- tt >> << ppppp hh hh ii tt >> pp pp ////////////////////////////// pp \\\\\\\\\\\\\\\ Phi-T(R) NeuroBayes(R) Teacher Algorithms by Michael Feindt Implementation by Phi-T Project 2001-2003 Copyright Phi-T GmbH Version 20080312 Library compiled with: NB_MAXPATTERN= 1500000 NB_MAXNODE = 100 ----------------------------------- found 16347 samples to learn from preprocessing flags/parameters: global preprocessing flag: 812 individual preprocessing: now perform preprocessing *** called with option 12 *** This will do for you: *** input variable equalisation *** to Gaussian distribution with mean=0 and sigma=1 *** Then variables are decorrelated ************************************ Warning: found 410 negative weights. Signal fraction: 73.1911011 % ------------------------------ Transdef: Tab for variable 1 -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. -1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. ------------------------------ Transdef: Tab for variable 2 56.6901665 62.6995163 63.3274155 67.3684464 68.4585724 69.7149506 71.3484955 71.6799316 73.9533386 75.231987 75.6971664 76.6545258 77.0368805 77.0652542 78.6552734 79.2816315 79.8802032 80.9676208 81.5576859 82.4033813 83.1850281 83.3777847 83.6588135 84.3928223 84.7511215 85.7316284 86.269249 86.6845856 87.5485764 88.0245132 88.6075058 89.0414124 90.1037521 91.029686 91.6196289 91.9677811 92.8241882 92.9190598 93.9088135 94.6829529 95.3681335 96.1719894 96.6819229 97.0310669 97.8211365 98.3959961 98.8496704 99.3559113 100.070465 100.671654 100.928719 101.629349 102.41803 103.73246 104.300591 105.178276 105.637924 106.336884 106.719284 107.370216 108.354156 109.092865 109.933472 110.930801 112.089264 113.353409 113.794647 115.139084 116.675117 118.20639 120.085754 121.672241 123.20536 125.151077 126.679497 128.588715 130.098419 132.371277 134.630341 136.312958 138.45108 140.803131 142.879379 145.564606 148.079193 150.832321 152.982544 156.099396 159.468704 161.925552 164.711945 168.606232 172.343048 177.396835 187.624512 194.289291 207.365784 222.215912 243.430908 282.116364 524.602539 ------------------------------ Transdef: Tab for variable 3 20.0002613 20.4531536 20.8414268 21.0753269 21.1756783 21.5002232 21.7413445 22.0196991 22.20401 22.3613167 22.6323814 22.8012867 22.8326073 22.9986286 23.3379841 23.6058826 23.6204128 23.8915482 24.2271614 24.5818939 24.8776569 25.0387058 25.257103 25.4261875 25.5702171 25.6541462 25.8939171 26.1126137 26.33284 26.5411873 26.7937431 27.0202999 27.1316757 27.2713051 27.5264149 27.7735596 28.0274429 28.1570168 28.33885 28.5390587 28.6597443 28.8410969 29.0408001 29.166275 29.3975105 29.6428299 29.7240143 29.7840118 29.9514027 30.0407028 30.2502747 30.5118599 30.7175598 31.0011215 31.2268257 31.5726357 31.7345467 31.9578857 32.179306 32.3343658 32.5681763 32.8395462 33.1134109 33.3747292 33.570282 33.68153 33.8409157 34.1424141 34.346714 34.5786362 34.8879852 35.1181946 35.3957787 35.491127 35.6706085 36.0565414 36.4112816 36.6676712 37.0054855 37.3144455 37.5846367 38.0271912 38.6043091 39.0194702 39.4365273 40.0313721 40.4231644 41.0208588 41.5290031 42.1918335 42.9732513 44.002964 45.3194771 46.0485573 47.0241089 47.8258972 50.5594101 52.5075607 57.1234436 65.5396576 109.76886 ------------------------------ Transdef: Tab for variable 4 10.0000381 10.1100712 10.1423016 10.1989746 10.3170757 10.3633575 10.4115944 10.4374104 10.4677868 10.502861 10.5468321 10.615324 10.6692696 10.750164 10.7969446 10.9004421 10.9254856 10.9773264 11.0331068 11.1190491 11.2312698 11.2839193 11.3808699 11.4343519 11.5049591 11.5767069 11.7054844 11.7680645 11.8479586 11.9671335 12.0331984 12.1436949 12.2491016 12.3345394 12.4289999 12.5172968 12.6314316 12.7418785 12.8300667 12.9640398 13.1329975 13.2552872 13.3698215 13.5454683 13.6091938 13.6176329 13.6873674 13.7456455 13.8058643 13.9200382 14.0706329 14.1936522 14.311821 14.4074955 14.5701141 14.7173405 14.7686043 14.9160471 15.0832205 15.1877193 15.319211 15.4752026 15.646656 15.8137751 15.9838905 16.1552715 16.3348961 16.5394516 16.7352772 16.8388863 16.9959412 17.2766762 17.5050201 17.7025013 17.9231491 18.0692329 18.4108772 18.6917934 19.1138668 19.2849731 19.6281128 20.0372124 20.1797485 20.3349628 20.5040684 20.7588825 20.9968796 21.1691513 21.3997383 21.666811 21.9241867 22.3819332 22.7314987 23.0324249 23.4520931 23.8858566 24.4332237 25.0507927 25.9525719 27.5155144 37.5577545 ------------------------------ Transdef: Tab for variable 5 2.10590816 2.88016176 3.1425271 3.34973574 3.53161955 3.67779875 3.77949858 3.90740156 4.03201675 4.12831116 4.21359539 4.32521677 4.46802235 4.52733278 4.58475208 4.65750408 4.71770048 4.79136992 4.84926319 4.91077232 4.96785688 5.0114212 5.11084843 5.14787674 5.1663332 5.22820759 5.2657671 5.30219936 5.34011221 5.4181509 5.47095442 5.49682093 5.53292036 5.53799629 5.56926489 5.65320396 5.71280193 5.74835873 5.81820297 5.88186741 5.92271328 5.98886776 6.03279018 6.10022449 6.15231514 6.20522881 6.23946857 6.28248072 6.30520821 6.34235859 6.39373398 6.43907356 6.49235058 6.548172 6.59892845 6.62745571 6.64399815 6.68022728 6.70563745 6.7531805 6.77705669 6.81221342 6.82868862 6.86456013 6.89028168 6.94224262 7.00741577 7.06432056 7.12504196 7.17116833 7.20760918 7.22281551 7.25250626 7.31262302 7.36244106 7.38016987 7.40696144 7.43495226 7.50509167 7.53175163 7.58119059 7.64604664 7.68358135 7.75445652 7.86243057 7.95454502 7.98833227 8.06002808 8.08599472 8.16476822 8.21062088 8.25381851 8.41209984 8.56494045 8.74302578 8.84539223 8.94648361 9.17317772 9.53061104 10.0389519 14.7243395 ------------------------------ Transdef: Tab for variable 6 25.0099258 25.8835754 26.5852394 27.3280792 28.1391563 29.0673218 29.5308037 30.4535599 31.1199512 31.1572723 31.8313065 32.2305565 32.5896606 32.8210831 33.3203125 33.8069229 34.1168594 34.5043869 34.8983994 35.1299744 35.7004509 35.9875107 36.1479568 36.7447701 37.241806 37.8948822 38.433548 38.7755585 39.1936722 39.6278076 40.0267563 40.3525772 40.6926727 40.9461441 41.4873962 41.8739548 42.1996002 42.422657 42.5671158 42.8677635 43.007576 43.1667824 43.5473595 43.8310089 43.8904839 44.0274773 44.3826981 44.7724457 45.1685791 45.3654633 45.5905228 45.7462196 45.9056244 46.2282944 46.6804962 46.9520111 47.1775475 47.5994415 47.9200134 48.1129608 48.237278 48.5807037 49.0050392 49.4194489 49.7629318 50.0529709 50.3404732 50.7523956 51.1160507 51.563446 51.9300461 52.2342224 52.6856346 53.4054565 53.7660294 54.168663 54.3576851 54.7747993 55.3553391 55.5632248 56.0969315 56.812561 57.3823547 58.0579529 58.4691544 59.2847366 59.600708 60.5252151 61.6498489 62.4996033 63.5979309 65.1946487 66.6934433 68.2211456 70.5126877 72.6523438 76.1596069 79.2244186 84.7226868 99.0461578 186.39682 ------------------------------ Transdef: Tab for variable 7 30.250906 31.6797562 33.6425018 33.7815361 34.5229416 35.0295334 35.5820541 36.2691422 36.7141304 37.6521378 38.2077255 38.5666008 38.8478394 38.8859253 39.0786667 39.6152763 40.0508194 40.16922 40.3372078 40.5354919 40.6618347 40.8995132 41.3237152 41.4486618 41.8000793 42.0958672 42.3257484 42.6423874 42.7324562 43.1770706 43.9470901 44.3321457 44.6018105 44.8805923 45.1099091 45.4655304 45.7124329 46.0028229 46.4199944 46.7624588 47.0244751 47.5616455 47.9689827 48.3368912 48.6364288 49.0839844 49.6905403 50.091713 50.6411743 51.0667877 51.6229897 52.0500183 52.5962257 53.176136 53.8250084 54.9578781 55.7500191 56.5908241 57.4449615 58.2241364 58.6142654 59.5395126 60.8623238 61.8428345 62.812603 63.6006088 65.388443 66.7360992 68.2941971 68.957901 70.2635498 70.8300247 72.8571014 74.5214539 75.6982117 76.8212128 78.5044708 79.8221359 81.3847351 83.9056625 86.2861023 87.8516388 89.7293015 92.1126709 93.8552704 96.0116272 97.7216187 100.199921 103.076157 105.551559 108.27182 111.505234 117.044037 120.935135 128.101669 134.508728 141.36911 149.220352 166.594894 186.373047 324.277283 ------------------------------ Transdef: Tab for variable 8 7.95799637 20.7817383 27.3065834 28.9010162 30.89188 31.3571548 31.9760418 32.9499664 33.3281937 33.7059174 33.9639511 34.7050972 35.0191193 35.4343529 35.6473999 36.1038971 36.6035767 37.2235146 37.5543442 37.7979927 38.0310745 38.5023422 38.6891098 38.8605347 38.9037628 39.1860504 39.2647972 39.3213196 39.5883179 39.6626968 39.7720108 39.8350258 39.9890213 40.3831444 40.7110939 40.7714119 41.1290359 41.27491 41.4311295 41.7467346 41.9477386 42.4083099 42.6809196 42.9197845 43.0869675 43.364872 43.6700172 43.7859039 44.1382179 44.4739075 44.7457886 44.8788986 45.1971512 45.4654427 45.7829971 45.9389877 46.3028412 46.5652199 46.8154297 47.1624908 47.4821854 47.7157669 48.126606 48.5668488 48.7957458 48.909214 49.2220306 49.6082726 50.0337448 50.2919159 50.6957169 51.0590286 51.495697 52.0350571 52.4368362 52.8560638 53.4601593 54.0032959 54.8193665 55.3499908 56.0746994 56.7301292 57.5658112 57.9635849 58.3227577 59.37957 60.1306458 61.260498 62.0794868 63.0496826 64.4114838 65.7987061 67.0757599 69.0709229 71.3179169 74.2467804 77.6990051 82.6692505 89.4533234 104.682693 217.593964 ------------------------------ Transdef: Tab for variable 9 56.6901665 62.6995163 62.8023148 66.3600464 67.3902969 68.4783173 70.0148621 70.7580872 71.666069 72.4150467 74.4447174 75.231987 75.5134888 76.3947449 76.8641815 77.0368805 77.4571991 78.6552734 79.1634674 79.5540771 80.2672272 80.9676208 81.580452 82.2342834 82.9374847 83.1981812 83.4115753 83.8200989 84.2870712 84.6559296 84.9297943 85.7538223 86.1930695 86.5702972 86.9473572 87.5457458 88.1805725 88.5829315 88.8310242 89.4308701 90.0910187 90.567276 90.9484863 91.475441 91.6899719 92.3748016 92.7368622 92.9190598 93.2090912 93.603035 94.026413 94.4927597 94.9193344 95.5810165 95.9246216 96.3186874 96.7696381 97.0310669 97.5108643 97.850174 98.2447968 98.7555542 99.0472565 99.4955597 100.016541 100.472778 100.832703 101.197823 101.682831 102.183342 102.944839 103.69252 104.134186 104.721397 105.239838 105.620598 106.074501 106.337883 106.941246 107.569717 108.154991 108.6707 109.545013 110.467651 111.189354 112.431778 113.574615 114.751411 116.083397 117.573174 119.025696 121.021179 122.965561 125.494553 128.310669 131.285004 135.669159 139.822891 148.858582 160.620514 282.530121 ------------------------------ Transdef: Tab for variable 10 0.115694568 0.798131227 1.06603289 1.26988995 1.3874079 1.50878167 1.63305521 1.74169993 1.82760251 1.89728284 1.94976842 1.98689771 2.04683304 2.09469461 2.13494205 2.18432736 2.23707676 2.29338408 2.33026981 2.36838531 2.41904593 2.4444654 2.47635889 2.50806236 2.53677297 2.56779194 2.57601023 2.60498953 2.63007784 2.65581322 2.67868376 2.70503664 2.72664213 2.75181437 2.76830816 2.79021883 2.8013649 2.82910967 2.83674765 2.84579849 2.85121965 2.85665274 2.86250019 2.87438917 2.88150501 2.88785362 2.8976419 2.90967798 2.92006183 2.92610216 2.9385047 2.95063448 2.95860147 2.96528196 2.97268963 2.98021555 2.98551226 2.98992372 2.99457312 3.00273776 3.00627589 3.01199651 3.01520514 3.01960611 3.02514291 3.0274806 3.03455687 3.03943205 3.0443294 3.04824018 3.05426908 3.05780029 3.06318045 3.06605053 3.0677104 3.07116866 3.07256556 3.07526827 3.07780647 3.08002186 3.085464 3.08891821 3.09183717 3.0946908 3.09884381 3.1016109 3.10444069 3.10893226 3.11084175 3.11269259 3.11315107 3.11525893 3.11953354 3.12109327 3.12481022 3.1283114 3.13116074 3.13225889 3.13402629 3.13768411 3.14158416 ------------------------------ Transdef: Tab for variable 11 0.000149250031 0.00721222162 0.0112676546 0.0180621743 0.0219431221 0.0332040787 0.0491790734 0.0584684052 0.0708253384 0.0794007778 0.0884101391 0.0946593285 0.103631467 0.108296871 0.122055769 0.130124629 0.141164303 0.151542947 0.158069074 0.165052891 0.1748631 0.180366218 0.188195109 0.19800663 0.206560224 0.217618465 0.233191967 0.234483466 0.246339545 0.259321451 0.264467955 0.275196075 0.285592258 0.294297248 0.301539391 0.313948721 0.322804689 0.331643999 0.33829394 0.345891714 0.354896694 0.363816619 0.367607594 0.373195648 0.37877357 0.38415122 0.389988244 0.391555727 0.39587307 0.402073503 0.408480167 0.410220683 0.413066387 0.417835593 0.421022147 0.425309896 0.42831862 0.433173895 0.438804388 0.442893326 0.446399212 0.447230726 0.452418953 0.455579638 0.459073067 0.466060281 0.467272043 0.472662628 0.475305319 0.482169181 0.489797652 0.49909699 0.507445574 0.513655424 0.520669281 0.530160546 0.53485775 0.544193208 0.551394999 0.562691569 0.571658015 0.578044653 0.583462358 0.592778563 0.601936042 0.604764938 0.608630717 0.613349915 0.624661803 0.63306582 0.64423418 0.649424076 0.650412917 0.661236286 0.680362225 0.703837991 0.728531778 0.774699807 0.798982859 0.868979871 1.11007142 ------------------------------ Transdef: Tab for variable 12 0.280899316 0.374612927 0.40558517 0.413445652 0.416200638 0.423500896 0.427250564 0.432246506 0.436518073 0.440167248 0.445200562 0.447407782 0.452370495 0.456799626 0.460068613 0.462801158 0.464847147 0.467928678 0.471672446 0.473967075 0.477783263 0.479752868 0.484789252 0.489104509 0.491185546 0.494623065 0.498298287 0.501826525 0.505311966 0.509039342 0.513529837 0.517472506 0.520573974 0.522149503 0.527088165 0.528921664 0.533296108 0.537676275 0.541181445 0.543827534 0.548074245 0.552530408 0.554792225 0.558676541 0.562036932 0.567568898 0.569926322 0.572798252 0.578490496 0.583406687 0.588309407 0.593409598 0.595855832 0.599031448 0.601825714 0.603413939 0.607742667 0.611032367 0.616317153 0.620397806 0.622381687 0.628071785 0.633038402 0.636374116 0.637510896 0.644279599 0.646134436 0.650794923 0.654622376 0.657048404 0.659711421 0.665945053 0.667308569 0.670796514 0.674078405 0.675567985 0.678513706 0.683249056 0.690250337 0.697673559 0.701031208 0.708372355 0.713229597 0.718221962 0.727438092 0.731953382 0.73790127 0.745529175 0.753825307 0.760523438 0.772709489 0.78578043 0.791908205 0.796464443 0.808064759 0.835000753 0.84794569 0.889053464 0.915789902 0.945877194 1.15372479 ------------------------------ Transdef: Tab for variable 13 20.1945629 22.3101349 23.1108704 23.5115871 23.8649483 24.4562836 24.9954643 25.3813343 25.8365612 26.1785164 26.7263069 26.9856491 27.3122559 27.5684128 28.0819397 28.3185196 28.852953 29.3216419 29.5638714 29.7035789 29.9776096 30.1981239 30.5140514 30.5765038 30.8518448 30.983242 31.3938599 31.7247314 32.0068283 32.3475838 32.6814766 33.1257248 33.4984818 33.9080086 34.2900543 34.5132904 34.8037338 35.0722885 35.4067612 35.5920105 35.9471779 36.1110153 36.5524483 36.9578552 37.3159332 37.8281479 38.3783417 38.5522614 38.899704 39.2321396 39.6041412 39.9277496 40.4661636 40.9517593 41.4342041 41.8632622 42.3292084 42.8481255 43.2658463 43.5045395 44.0846977 44.5854874 45.0937119 45.9074898 46.361763 46.5369186 47.1700134 47.6771545 48.4690895 49.1485405 50.0236626 50.7774124 51.0829659 51.8366776 52.6130714 53.4732513 54.7256775 55.7090988 57.1629524 58.612793 59.4360466 60.085907 60.9419403 62.1658707 63.514389 64.4362869 66.365593 66.7288513 67.3924789 69.2943573 72.3620911 74.5577774 76.6716156 78.7514648 81.0027466 82.9963379 85.7759705 89.4456635 92.9634933 103.987488 192.369995 ------------------------------ Transdef: Tab for variable 14 10.0685101 10.4301186 10.4772854 10.6135683 10.8928919 10.9244976 11.1299782 11.3893986 11.5736408 11.6953602 11.8886633 12.1407928 12.3127937 12.4683399 12.6549587 13.0181675 13.2906933 13.5920696 13.6996641 13.8520184 13.9055367 14.1227551 14.4400425 14.6181011 14.866066 15.0519619 15.2026215 15.3843508 15.6430798 15.8535137 16.0774078 16.2626686 16.3837013 16.5297203 16.7061691 16.7812729 16.9066887 17.0599499 17.288702 17.620348 17.7361488 17.8613586 17.9861221 18.183197 18.3662949 18.5100327 18.624548 18.7505093 19.0044518 19.2518578 19.4829025 19.6103401 19.7994938 19.8765163 20.0664444 20.2607193 20.4505634 20.5775337 20.7929573 20.998127 21.2034512 21.5309925 21.6449051 21.7373791 21.8782749 22.1259384 22.3430672 22.5844765 22.8064232 23.1151581 23.2934761 23.4855881 23.6700401 23.9920692 24.3204651 24.5519714 24.8562698 25.1039371 25.4684448 25.8930588 26.0999947 26.4925194 26.8578491 27.3109474 27.6366234 28.1761436 28.4862461 29.2466869 29.5271721 30.2888565 30.9610252 31.5744076 32.2000275 33.4366875 34.2558708 35.7045021 37.0666809 39.0708847 42.7811813 53.1575775 89.625824 COVARIANCE MATRIX (IN PERCENT) 0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 0 0.9 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1 100.0 41.0 22.7 18.9 -12.0 14.0 44.7 27.3 31.4 -33.3 -1.4 -9.9 7.6 13.7 2 41.0 100.0 51.9 32.4 6.1 54.9 93.4 60.2 85.5 -56.1 -10.8 -29.0 21.9 18.7 3 22.7 51.9 100.0 3.0 -13.6 16.8 56.3 38.8 60.4 -15.6 -11.2 -33.3 58.9 -2.4 4 18.9 32.4 3.0 100.0 -10.0 7.9 36.9 25.6 34.0 -12.5 -19.8 -40.0 -2.7 73.9 5 -12.0 6.1 -13.6 -10.0 100.0 77.8 -23.8 29.7 41.5 33.5 1.8 8.7 -11.8 -11.3 6 14.0 54.9 16.8 7.9 77.8 100.0 29.5 61.1 76.3 -1.9 -3.7 -7.9 3.0 0.6 7 44.7 93.4 56.3 36.9 -23.8 29.5 100.0 55.9 71.0 -62.5 -11.6 -30.9 25.4 22.7 8 27.3 60.2 38.8 25.6 29.7 61.1 55.9 100.0 71.2 -13.2 -12.0 -20.2 18.1 16.1 9 31.4 85.5 60.4 34.0 41.5 76.3 71.0 71.2 100.0 -26.2 -12.7 -32.8 27.9 19.7 10 -33.3 -56.1 -15.6 -12.5 33.5 -1.9 -62.5 -13.2 -26.2 100.0 -3.7 3.4 -2.1 -4.7 11 -1.4 -10.8 -11.2 -19.8 1.8 -3.7 -11.6 -12.0 -12.7 -3.7 100.0 46.8 -11.3 -19.1 12 -9.9 -29.0 -33.3 -40.0 8.7 -7.9 -30.9 -20.2 -32.8 3.4 46.8 100.0 -17.1 -33.2 13 7.6 21.9 58.9 -2.7 -11.8 3.0 25.4 18.1 27.9 -2.1 -11.3 -17.1 100.0 26.7 14 13.7 18.7 -2.4 73.9 -11.3 0.6 22.7 16.1 19.7 -4.7 -19.1 -33.2 26.7 100.0 TOTAL CORRELATION TO TARGET (diagonal) 89.9096696 TOTAL CORRELATION OF ALL VARIABLES 46.7865665 ROUND 1: MAX CORR ( 46.7856442) AFTER KILLING INPUT VARIABLE 3 CONTR 0.293779653 ROUND 2: MAX CORR ( 46.7556113) AFTER KILLING INPUT VARIABLE 11 CONTR 1.67610006 ROUND 3: MAX CORR ( 46.7070274) AFTER KILLING INPUT VARIABLE 8 CONTR 2.1309097 ROUND 4: MAX CORR ( 46.6366076) AFTER KILLING INPUT VARIABLE 4 CONTR 2.56383352 ROUND 5: MAX CORR ( 46.4031648) AFTER KILLING INPUT VARIABLE 5 CONTR 4.6604148 ROUND 6: MAX CORR ( 46.2811847) AFTER KILLING INPUT VARIABLE 6 CONTR 3.3623871 ROUND 7: MAX CORR ( 46.0242003) AFTER KILLING INPUT VARIABLE 12 CONTR 4.87042525 ROUND 8: MAX CORR ( 45.7987127) AFTER KILLING INPUT VARIABLE 14 CONTR 4.55026657 ROUND 9: MAX CORR ( 45.6119577) AFTER KILLING INPUT VARIABLE 13 CONTR 4.13175536 ROUND 10: MAX CORR ( 45.3142636) AFTER KILLING INPUT VARIABLE 2 CONTR 5.2027108 ROUND 11: MAX CORR ( 45.2754799) AFTER KILLING INPUT VARIABLE 9 CONTR 1.87440883 ROUND 12: MAX CORR ( 44.7499248) AFTER KILLING INPUT VARIABLE 10 CONTR 6.87846729 LAST REMAINING VARIABLE: 7 total correlation to target: 46.7865665 % total significance: 22.8514703 sigma correlations of single variables to target: variable 2: 40.9778915 % , in sigma: 20.0144003 variable 3: 22.6506797 % , in sigma: 11.0630331 variable 4: 18.9005647 % , in sigma: 9.23140391 variable 5: -12.0193445 % , in sigma: 5.87048196 variable 6: 14.0476917 % , in sigma: 6.86116623 variable 7: 44.7499248 % , in sigma: 21.8567348 variable 8: 27.3070542 % , in sigma: 13.3372971 variable 9: 31.3991373 % , in sigma: 15.3359502 variable 10: -33.3491837 % , in sigma: 16.2883908 variable 11: -1.38222588 % , in sigma: 0.675106039 variable 12: -9.90340539 % , in sigma: 4.83701606 variable 13: 7.64962944 % , in sigma: 3.736228 variable 14: 13.6990689 % , in sigma: 6.69089207 variables sorted by significance: 1 most relevant variable 7 corr 44.7499237 , in sigma: 21.8567343 2 most relevant variable 10 corr 6.87846708 , in sigma: 3.35957729 3 most relevant variable 9 corr 1.87440884 , in sigma: 0.915497783 4 most relevant variable 2 corr 5.20271063 , in sigma: 2.5411052 5 most relevant variable 13 corr 4.13175535 , in sigma: 2.01802978 6 most relevant variable 14 corr 4.55026674 , in sigma: 2.2224389 7 most relevant variable 12 corr 4.87042522 , in sigma: 2.37881053 8 most relevant variable 6 corr 3.36238718 , in sigma: 1.64225538 9 most relevant variable 5 corr 4.6604147 , in sigma: 2.2762373 10 most relevant variable 4 corr 2.56383348 , in sigma: 1.2522262 11 most relevant variable 8 corr 2.13090968 , in sigma: 1.04077779 12 most relevant variable 11 corr 1.67610002 , in sigma: 0.818639891 13 most relevant variable 3 corr 0.293779641 , in sigma: 0.143487698 global correlations between input variables: variable 2: 98.7558873 % variable 3: 92.8044732 % variable 4: 86.8409088 % variable 5: 95.5675938 % variable 6: 93.7584216 % variable 7: 98.5775875 % variable 8: 80.9860228 % variable 9: 98.3992149 % variable 10: 74.5845707 % variable 11: 48.3499499 % variable 12: 64.3291921 % variable 13: 76.0168476 % variable 14: 84.1315132 % significance loss when removing single variables: variable 2: corr = 3.9861073 % , sigma = 1.94689244 variable 3: corr = 0.293779653 % , sigma = 0.143487704 variable 4: corr = 2.21666529 % , sigma = 1.0826625 variable 5: corr = 4.34479659 % , sigma = 2.12208327 variable 6: corr = 4.30267579 % , sigma = 2.10151065 variable 7: corr = 7.25735386 % , sigma = 3.54463297 variable 8: corr = 2.25025628 % , sigma = 1.09906899 variable 9: corr = 2.93745139 % , sigma = 1.43470847 variable 10: corr = 7.19357868 % , sigma = 3.51348393 variable 11: corr = 1.67056668 % , sigma = 0.815937301 variable 12: corr = 3.32931554 % , sigma = 1.62610255 variable 13: corr = 4.96340831 % , sigma = 2.42422528 variable 14: corr = 5.22802355 % , sigma = 2.55346852 Keep only 2 most significant input variables ------------------------------------- Teacher: actual network topology: Nodes(1) = 3 Nodes(2) = 15 Nodes(3) = 1 ------------------------------------- --------------------------------------------------- Iteration : 1 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 2 --> 9.17780781 sigma out 15 active outputs RANK 2 NODE 1 --> 7.38922501 sigma out 15 active outputs RANK 3 NODE 3 --> 7.19883156 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 12 --> 10.1081266 sigma in 3act. ( 10.89643 sig out 1act.) RANK 2 NODE 7 --> 4.80629349 sigma in 3act. ( 4.97064018 sig out 1act.) RANK 3 NODE 6 --> 4.60181475 sigma in 3act. ( 5.61789703 sig out 1act.) RANK 4 NODE 2 --> 4.11240768 sigma in 3act. ( 4.46911812 sig out 1act.) RANK 5 NODE 8 --> 3.18506074 sigma in 3act. ( 3.76674342 sig out 1act.) RANK 6 NODE 13 --> 2.61925244 sigma in 3act. ( 3.27449322 sig out 1act.) RANK 7 NODE 14 --> 2.06821227 sigma in 3act. ( 2.69074726 sig out 1act.) RANK 8 NODE 11 --> 1.09134603 sigma in 3act. ( 1.17072308 sig out 1act.) RANK 9 NODE 4 --> 1.0602771 sigma in 3act. ( 1.03179586 sig out 1act.) RANK 10 NODE 9 --> 1.04187953 sigma in 3act. ( 0.883850813 sig out 1act.) RANK 11 NODE 3 --> 0.839259863 sigma in 3act. ( 1.06624544 sig out 1act.) RANK 12 NODE 10 --> 0.797536254 sigma in 3act. ( 1.24406219 sig out 1act.) RANK 13 NODE 5 --> 0.770932496 sigma in 3act. ( 0.0427227095 sig out 1act.) RANK 14 NODE 15 --> 0.731833398 sigma in 3act. ( 0.18974869 sig out 1act.) RANK 15 NODE 1 --> 0.372857839 sigma in 3act. ( 0.173000142 sig out 1act.) sorted by output significance RANK 1 NODE 12 --> 10.89643 sigma out 1act.( 10.1081266 sig in 3act.) RANK 2 NODE 6 --> 5.61789703 sigma out 1act.( 4.60181475 sig in 3act.) RANK 3 NODE 7 --> 4.97064018 sigma out 1act.( 4.80629349 sig in 3act.) RANK 4 NODE 2 --> 4.46911812 sigma out 1act.( 4.11240768 sig in 3act.) RANK 5 NODE 8 --> 3.76674342 sigma out 1act.( 3.18506074 sig in 3act.) RANK 6 NODE 13 --> 3.27449322 sigma out 1act.( 2.61925244 sig in 3act.) RANK 7 NODE 14 --> 2.69074726 sigma out 1act.( 2.06821227 sig in 3act.) RANK 8 NODE 10 --> 1.24406219 sigma out 1act.( 0.797536254 sig in 3act.) RANK 9 NODE 11 --> 1.17072308 sigma out 1act.( 1.09134603 sig in 3act.) RANK 10 NODE 3 --> 1.06624544 sigma out 1act.( 0.839259863 sig in 3act.) RANK 11 NODE 4 --> 1.03179586 sigma out 1act.( 1.0602771 sig in 3act.) RANK 12 NODE 9 --> 0.883850813 sigma out 1act.( 1.04187953 sig in 3act.) RANK 13 NODE 15 --> 0.18974869 sigma out 1act.( 0.731833398 sig in 3act.) RANK 14 NODE 1 --> 0.173000142 sigma out 1act.( 0.372857839 sig in 3act.) RANK 15 NODE 5 --> 0.0427227095 sigma out 1act.( 0.770932496 sig in 3act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 15.267375 sigma in 15 active inputs SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 11.2381563 sigma out 15 active outputs RANK 2 NODE 2 --> 10.4985876 sigma out 15 active outputs RANK 3 NODE 3 --> 8.45523071 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 12 --> 10.0136471 sigma in 3act. ( 9.81034374 sig out 1act.) RANK 2 NODE 2 --> 6.3550148 sigma in 3act. ( 5.41984987 sig out 1act.) RANK 3 NODE 7 --> 6.14834738 sigma in 3act. ( 5.85873032 sig out 1act.) RANK 4 NODE 8 --> 4.93622065 sigma in 3act. ( 4.36231184 sig out 1act.) RANK 5 NODE 9 --> 4.68944359 sigma in 3act. ( 2.5383091 sig out 1act.) RANK 6 NODE 4 --> 4.25659609 sigma in 3act. ( 1.77896237 sig out 1act.) RANK 7 NODE 6 --> 3.87510824 sigma in 3act. ( 5.89512873 sig out 1act.) RANK 8 NODE 13 --> 3.27180743 sigma in 3act. ( 3.07037926 sig out 1act.) RANK 9 NODE 11 --> 3.0451138 sigma in 3act. ( 1.44201124 sig out 1act.) RANK 10 NODE 14 --> 2.99045181 sigma in 3act. ( 2.52979016 sig out 1act.) RANK 11 NODE 3 --> 2.97193694 sigma in 3act. ( 2.52517986 sig out 1act.) RANK 12 NODE 15 --> 2.63317657 sigma in 3act. ( 0.668130338 sig out 1act.) RANK 13 NODE 5 --> 1.63365149 sigma in 3act. ( 0.141221717 sig out 1act.) RANK 14 NODE 10 --> 1.40361738 sigma in 3act. ( 1.89116311 sig out 1act.) RANK 15 NODE 1 --> 0.853484452 sigma in 3act. ( 0.152071163 sig out 1act.) sorted by output significance RANK 1 NODE 12 --> 9.81034374 sigma out 1act.( 10.0136471 sig in 3act.) RANK 2 NODE 6 --> 5.89512873 sigma out 1act.( 3.87510824 sig in 3act.) RANK 3 NODE 7 --> 5.85873032 sigma out 1act.( 6.14834738 sig in 3act.) RANK 4 NODE 2 --> 5.41984987 sigma out 1act.( 6.3550148 sig in 3act.) RANK 5 NODE 8 --> 4.36231184 sigma out 1act.( 4.93622065 sig in 3act.) RANK 6 NODE 13 --> 3.07037926 sigma out 1act.( 3.27180743 sig in 3act.) RANK 7 NODE 9 --> 2.5383091 sigma out 1act.( 4.68944359 sig in 3act.) RANK 8 NODE 14 --> 2.52979016 sigma out 1act.( 2.99045181 sig in 3act.) RANK 9 NODE 3 --> 2.52517986 sigma out 1act.( 2.97193694 sig in 3act.) RANK 10 NODE 10 --> 1.89116311 sigma out 1act.( 1.40361738 sig in 3act.) RANK 11 NODE 4 --> 1.77896237 sigma out 1act.( 4.25659609 sig in 3act.) RANK 12 NODE 11 --> 1.44201124 sigma out 1act.( 3.0451138 sig in 3act.) RANK 13 NODE 15 --> 0.668130338 sigma out 1act.( 2.63317657 sig in 3act.) RANK 14 NODE 1 --> 0.152071163 sigma out 1act.( 0.853484452 sig in 3act.) RANK 15 NODE 5 --> 0.141221717 sigma out 1act.( 1.63365149 sig in 3act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 15.8644676 sigma in 15 active inputs *********************************************** *** Learn Path 1 *** loss function: -0.508294344 *** contribution from regularisation: 0.0117268553 *** contribution from error: -0.5200212 *********************************************** -----------------> Test sample --------------------------------------------------- Iteration : 2 *********************************************** *** Learn Path 2 *** loss function: -0.537457287 *** contribution from regularisation: 0.00710903946 *** contribution from error: -0.544566333 *********************************************** -----------------> Test sample ENTER BFGS code START -4393.4556 -1.14669776 0.28136003 EXIT FROM BFGS code FG_START 0. -1.14669776 0. --------------------------------------------------- Iteration : 3 *********************************************** *** Learn Path 3 *** loss function: -0.544385552 *** contribution from regularisation: 0.00415574247 *** contribution from error: -0.548541307 *********************************************** -----------------> Test sample ENTER BFGS code FG_START -4449.26292 -1.14669776 -7.52541637 EXIT FROM BFGS code FG_LNSRCH 0. -1.1973139 0. --------------------------------------------------- Iteration : 4 *********************************************** *** Learn Path 4 *** loss function: -0.542416215 *** contribution from regularisation: 0.00710496679 *** contribution from error: -0.549521208 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4433.16789 -1.1973139 33.9559402 EXIT FROM BFGS code FG_LNSRCH 0. -1.167961 0. --------------------------------------------------- Iteration : 5 *********************************************** *** Learn Path 5 *** loss function: -0.550012887 *** contribution from regularisation: 0.00645894837 *** contribution from error: -0.556471825 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4495.25545 -1.167961 6.89834595 EXIT FROM BFGS code NEW_X -4495.25545 -1.167961 6.89834595 ENTER BFGS code NEW_X -4495.25545 -1.167961 6.89834595 EXIT FROM BFGS code FG_LNSRCH 0. -1.15310574 0. --------------------------------------------------- Iteration : 6 *********************************************** *** Learn Path 6 *** loss function: -0.551043212 *** contribution from regularisation: 0.00663373526 *** contribution from error: -0.557676971 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4503.67622 -1.15310574 5.73318481 EXIT FROM BFGS code NEW_X -4503.67622 -1.15310574 5.73318481 ENTER BFGS code NEW_X -4503.67622 -1.15310574 5.73318481 EXIT FROM BFGS code FG_LNSRCH 0. -1.1008482 0. --------------------------------------------------- Iteration : 7 *********************************************** *** Learn Path 7 *** loss function: -0.55139786 *** contribution from regularisation: 0.00717501668 *** contribution from error: -0.558572888 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4506.57466 -1.1008482 3.7109561 EXIT FROM BFGS code NEW_X -4506.57466 -1.1008482 3.7109561 ENTER BFGS code NEW_X -4506.57466 -1.1008482 3.7109561 EXIT FROM BFGS code FG_LNSRCH 0. -1.07183993 0. --------------------------------------------------- Iteration : 8 *********************************************** *** Learn Path 8 *** loss function: -0.551664352 *** contribution from regularisation: 0.00702087814 *** contribution from error: -0.558685243 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4508.75294 -1.07183993 3.89176273 EXIT FROM BFGS code FG_LNSRCH 0. -0.955806971 0. --------------------------------------------------- Iteration : 9 *********************************************** *** Learn Path 9 *** loss function: -0.552596331 *** contribution from regularisation: 0.00609865692 *** contribution from error: -0.558694959 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4516.37001 -0.955806971 5.37769461 EXIT FROM BFGS code NEW_X -4516.37001 -0.955806971 5.37769461 ENTER BFGS code NEW_X -4516.37001 -0.955806971 5.37769461 EXIT FROM BFGS code FG_LNSRCH 0. -0.329330921 0. --------------------------------------------------- Iteration : 10 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 3 --> 6.09157896 sigma out 15 active outputs RANK 2 NODE 1 --> 4.9665246 sigma out 15 active outputs RANK 3 NODE 2 --> 3.04811025 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 6 --> 3.76103115 sigma in 3act. ( 2.32484221 sig out 1act.) RANK 2 NODE 7 --> 3.68152189 sigma in 3act. ( 3.35737252 sig out 1act.) RANK 3 NODE 9 --> 2.8271966 sigma in 3act. ( 3.50726819 sig out 1act.) RANK 4 NODE 2 --> 2.70736313 sigma in 3act. ( 2.53741241 sig out 1act.) RANK 5 NODE 4 --> 2.4029479 sigma in 3act. ( 3.39189219 sig out 1act.) RANK 6 NODE 3 --> 2.07365584 sigma in 3act. ( 1.54446459 sig out 1act.) RANK 7 NODE 14 --> 2.06354237 sigma in 3act. ( 2.48182297 sig out 1act.) RANK 8 NODE 8 --> 1.74593973 sigma in 3act. ( 0.640325487 sig out 1act.) RANK 9 NODE 15 --> 1.67250621 sigma in 3act. ( 2.13496208 sig out 1act.) RANK 10 NODE 10 --> 1.56571293 sigma in 3act. ( 0.639895678 sig out 1act.) RANK 11 NODE 13 --> 1.51329207 sigma in 3act. ( 1.13144171 sig out 1act.) RANK 12 NODE 11 --> 1.33607924 sigma in 3act. ( 1.08832073 sig out 1act.) RANK 13 NODE 12 --> 0.79498297 sigma in 3act. ( 0.857047379 sig out 1act.) RANK 14 NODE 5 --> 0.666810751 sigma in 3act. ( 0.596618712 sig out 1act.) RANK 15 NODE 1 --> 0.511478722 sigma in 3act. ( 0.652035177 sig out 1act.) sorted by output significance RANK 1 NODE 9 --> 3.50726819 sigma out 1act.( 2.8271966 sig in 3act.) RANK 2 NODE 4 --> 3.39189219 sigma out 1act.( 2.4029479 sig in 3act.) RANK 3 NODE 7 --> 3.35737252 sigma out 1act.( 3.68152189 sig in 3act.) RANK 4 NODE 2 --> 2.53741241 sigma out 1act.( 2.70736313 sig in 3act.) RANK 5 NODE 14 --> 2.48182297 sigma out 1act.( 2.06354237 sig in 3act.) RANK 6 NODE 6 --> 2.32484221 sigma out 1act.( 3.76103115 sig in 3act.) RANK 7 NODE 15 --> 2.13496208 sigma out 1act.( 1.67250621 sig in 3act.) RANK 8 NODE 3 --> 1.54446459 sigma out 1act.( 2.07365584 sig in 3act.) RANK 9 NODE 13 --> 1.13144171 sigma out 1act.( 1.51329207 sig in 3act.) RANK 10 NODE 11 --> 1.08832073 sigma out 1act.( 1.33607924 sig in 3act.) RANK 11 NODE 12 --> 0.857047379 sigma out 1act.( 0.79498297 sig in 3act.) RANK 12 NODE 1 --> 0.652035177 sigma out 1act.( 0.511478722 sig in 3act.) RANK 13 NODE 8 --> 0.640325487 sigma out 1act.( 1.74593973 sig in 3act.) RANK 14 NODE 10 --> 0.639895678 sigma out 1act.( 1.56571293 sig in 3act.) RANK 15 NODE 5 --> 0.596618712 sigma out 1act.( 0.666810751 sig in 3act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 8.05132008 sigma in 15 active inputs *********************************************** *** Learn Path 10 *** loss function: -0.541949093 *** contribution from regularisation: 0.00454901112 *** contribution from error: -0.54649812 *********************************************** -----------------> Test sample Iteration No: 10 ********************************************** ***** write out current network **** ***** to "rescue.nb" **** ********************************************** SAVING EXPERTISE TO rescue.nb ENTER BFGS code FG_LNSRCH -4429.34997 -0.329330921 -19.7556076 EXIT FROM BFGS code FG_LNSRCH 0. -0.860649884 0. --------------------------------------------------- Iteration : 11 *********************************************** *** Learn Path 11 *** loss function: -0.546188653 *** contribution from regularisation: 0.0122629674 *** contribution from error: -0.558451593 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4463.9997 -0.860649884 1.06749725 EXIT FROM BFGS code FG_LNSRCH 0. -0.953630209 0. --------------------------------------------------- Iteration : 12 *********************************************** *** Learn Path 12 *** loss function: -0.552900255 *** contribution from regularisation: 0.00579286413 *** contribution from error: -0.558693111 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4518.85376 -0.953630209 6.34672546 EXIT FROM BFGS code FG_LNSRCH 0. -0.951527894 0. --------------------------------------------------- Iteration : 13 *********************************************** *** Learn Path 13 *** loss function: -0.551366866 *** contribution from regularisation: 0.00732355053 *** contribution from error: -0.558690429 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4506.32128 -0.951527894 3.95150995 EXIT FROM BFGS code FG_LNSRCH 0. -0.953625143 0. --------------------------------------------------- Iteration : 14 *********************************************** *** Learn Path 14 *** loss function: -0.552373469 *** contribution from regularisation: 0.00631964253 *** contribution from error: -0.558693111 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4514.54836 -0.953625143 5.11820507 EXIT FROM BFGS code FG_LNSRCH 0. -0.953630209 0. --------------------------------------------------- Iteration : 15 *********************************************** *** Learn Path 15 *** loss function: -0.551981568 *** contribution from regularisation: 0.00671151793 *** contribution from error: -0.558693111 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4511.3456 -0.953630209 4.82086992 EXIT FROM BFGS code NEW_X -4511.3456 -0.953630209 4.82086992 ENTER BFGS code NEW_X -4511.3456 -0.953630209 4.82086992 EXIT FROM BFGS code CONVERGENC -4511.3456 -0.953630209 4.82086992 --------------------------------------------------- Iteration : 250 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 13.4863691 sigma out 15 active outputs RANK 2 NODE 3 --> 10.6665192 sigma out 15 active outputs RANK 3 NODE 2 --> 9.14928341 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 7 --> 8.21551609 sigma in 3act. ( 6.08444595 sig out 1act.) RANK 2 NODE 2 --> 7.8841114 sigma in 3act. ( 6.0283742 sig out 1act.) RANK 3 NODE 9 --> 7.82990408 sigma in 3act. ( 5.693964 sig out 1act.) RANK 4 NODE 12 --> 7.66144514 sigma in 3act. ( 7.70956469 sig out 1act.) RANK 5 NODE 4 --> 6.46565628 sigma in 3act. ( 4.81866884 sig out 1act.) RANK 6 NODE 8 --> 3.96808958 sigma in 3act. ( 3.18333602 sig out 1act.) RANK 7 NODE 3 --> 3.9657445 sigma in 3act. ( 3.27836823 sig out 1act.) RANK 8 NODE 14 --> 3.89462233 sigma in 3act. ( 3.42357874 sig out 1act.) RANK 9 NODE 13 --> 3.36028886 sigma in 3act. ( 2.89314604 sig out 1act.) RANK 10 NODE 15 --> 3.11245203 sigma in 3act. ( 2.47875261 sig out 1act.) RANK 11 NODE 11 --> 2.65938616 sigma in 3act. ( 2.09603882 sig out 1act.) RANK 12 NODE 6 --> 2.52228022 sigma in 3act. ( 2.30901217 sig out 1act.) RANK 13 NODE 10 --> 2.18831182 sigma in 3act. ( 1.652192 sig out 1act.) RANK 14 NODE 5 --> 1.23135006 sigma in 3act. ( 0.759130359 sig out 1act.) RANK 15 NODE 1 --> 0.737139881 sigma in 3act. ( 0.523457468 sig out 1act.) sorted by output significance RANK 1 NODE 12 --> 7.70956469 sigma out 1act.( 7.66144514 sig in 3act.) RANK 2 NODE 7 --> 6.08444595 sigma out 1act.( 8.21551609 sig in 3act.) RANK 3 NODE 2 --> 6.0283742 sigma out 1act.( 7.8841114 sig in 3act.) RANK 4 NODE 9 --> 5.693964 sigma out 1act.( 7.82990408 sig in 3act.) RANK 5 NODE 4 --> 4.81866884 sigma out 1act.( 6.46565628 sig in 3act.) RANK 6 NODE 14 --> 3.42357874 sigma out 1act.( 3.89462233 sig in 3act.) RANK 7 NODE 3 --> 3.27836823 sigma out 1act.( 3.9657445 sig in 3act.) RANK 8 NODE 8 --> 3.18333602 sigma out 1act.( 3.96808958 sig in 3act.) RANK 9 NODE 13 --> 2.89314604 sigma out 1act.( 3.36028886 sig in 3act.) RANK 10 NODE 15 --> 2.47875261 sigma out 1act.( 3.11245203 sig in 3act.) RANK 11 NODE 6 --> 2.30901217 sigma out 1act.( 2.52228022 sig in 3act.) RANK 12 NODE 11 --> 2.09603882 sigma out 1act.( 2.65938616 sig in 3act.) RANK 13 NODE 10 --> 1.652192 sigma out 1act.( 2.18831182 sig in 3act.) RANK 14 NODE 5 --> 0.759130359 sigma out 1act.( 1.23135006 sig in 3act.) RANK 15 NODE 1 --> 0.523457468 sigma out 1act.( 0.737139881 sig in 3act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 15.7753487 sigma in 15 active inputs *********************************************** *** Learn Path 250 *** loss function: -0.552034557 *** contribution from regularisation: 0.00665854011 *** contribution from error: -0.558693111 *********************************************** -----------------> Test sample END OF LEARNING , export EXPERTISE SAVING EXPERTISE TO expert.nb NB_AHISTOUT: storage space 22130 Closing output file done