NNInput NNInputs_155.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= 11963 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 = 3196 nbkg = 8767 Bkg Entries: 8767 Sig Entries: 3196 Chosen entries: 3196 Warning: entries low (below 6000) Signal fraction: 1 Background fraction: 0.364549 Signal Tree Copy Condition: Background Tree Copy Condition: Actual Background Entries: 8767 Actual Signal Entries: 3196 Entries to split: 3196 Test with : 1598 Train with : 1598 ********************************************* * 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= 3196 for Signal Prepared event 0 for Signal with 3196 events ====Entry 0 Variable Ht : 99.9033 Variable LepAPt : 45.9997 Variable LepBPt : 10.4729 Variable MetSigLeptonsJets : 5.77928 Variable MetSpec : 43.4303 Variable SumEtLeptonsJets : 56.4726 Variable VSumJetLeptonsPt : 55.0573 Variable addEt : 99.9033 Variable dPhiLepSumMet : 3.12902 Variable dPhiLeptons : 0.580524 Variable dRLeptons : 0.634439 Variable lep1_E : 64.933 Variable lep2_E : 17.9705 ===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 = 2155 Ht = 99.9033 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 45.9998 LepAPt = 45.9997 LepBEt = 10.4732 LepBPt = 10.4729 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 43.4303 MetDelPhi = 2.67816 MetSig = 3.76955 MetSigLeptonsJets = 5.77928 MetSpec = 43.4303 Mjj = 0 MostCentralJetEta = 0 MtllMet = 110.942 Njets = 0 SB = 0 SumEt = 132.741 SumEtJets = 0 SumEtLeptonsJets = 56.4726 Target = 1 TrainWeight = 1 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 55.0573 addEt = 99.9033 dPhiLepSumMet = 3.12902 dPhiLeptons = 0.580524 dRLeptons = 0.634439 diltype = 81 dimass = 13.7727 event = 820 jet1_Et = 0 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 64.933 lep2_E = 17.9705 rand = 0.999742 run = 236780 weight = 3.55492e-06 ===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= 8767 for Background Prepared event 0 for Background with 8767 events ====Entry 0 Variable Ht : 79.7868 Variable LepAPt : 30.5457 Variable LepBPt : 11.4206 Variable MetSigLeptonsJets : 5.83799 Variable MetSpec : 37.8193 Variable SumEtLeptonsJets : 41.9663 Variable VSumJetLeptonsPt : 41.2152 Variable addEt : 79.7868 Variable dPhiLepSumMet : 2.89654 Variable dPhiLeptons : 0.426439 Variable dRLeptons : 0.500605 Variable lep1_E : 30.5607 Variable lep2_E : 11.7282 ===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 = 79.7868 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 30.546 LepAPt = 30.5457 LepBEt = 11.4214 LepBPt = 11.4206 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 37.8193 MetDelPhi = 2.58497 MetSig = 2.81024 MetSigLeptonsJets = 5.83799 MetSpec = 37.8193 Mjj = 0 MostCentralJetEta = 0 MtllMet = 80.0898 Njets = 0 SB = 0 SumEt = 181.11 SumEtJets = 0 SumEtLeptonsJets = 41.9663 Target = 0 TrainWeight = 4.06348 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 41.2152 addEt = 79.7868 dPhiLepSumMet = 2.89654 dPhiLeptons = 0.426439 dRLeptons = 0.500605 diltype = 41 dimass = 9.31149 event = 6639571 jet1_Et = 0 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 30.5607 lep2_E = 11.7282 rand = 0.999742 run = 271566 weight = 0.0400324 ===Show End Warning: found 303 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 11963 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 303 negative weights. Signal fraction: 67.3689499 % ------------------------------ 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 56.5035744 61.4185257 68.2527466 68.3380432 68.6114044 70.2088394 70.7533112 73.9499969 76.0569534 78.7032166 79.4276733 80.6520996 81.0223618 81.3008423 82.4259949 84.501564 84.5345917 85.6835022 86.6975861 88.5156555 88.9060822 89.2397995 89.2848206 90.744339 91.6173019 91.9374695 92.0004578 92.7354431 93.1037521 94.5336914 96.3663101 97.2838669 97.4143219 99.3495789 100.471672 101.540909 102.124611 103.003693 104.684219 105.925049 105.949974 106.271088 106.430672 107.844742 108.782173 109.199554 109.817162 110.178757 110.81514 112.61348 113.76709 114.674774 115.969933 116.258423 117.478287 118.782639 120.037888 121.001007 121.235825 122.413422 123.500504 125.014862 126.510384 127.592041 128.797821 130.02652 131.365326 132.960938 134.457703 135.94812 137.25174 138.344879 139.282562 140.510559 141.853943 143.571686 145.122437 146.99884 148.139038 148.665863 150.806396 152.156403 154.508026 156.27272 158.531708 161.503937 164.513184 167.441986 171.383179 176.317642 179.32254 182.529984 187.186584 192.627472 199.616608 205.872559 213.538727 224.556686 234.701843 274.623352 484.526825 ------------------------------ Transdef: Tab for variable 3 20.0055256 20.1094894 20.4566765 20.7560501 21.4181252 21.4190178 22.0419044 22.4324875 22.7517109 22.8639984 23.2076855 23.4435711 23.5912209 23.772831 24.118103 24.4307423 24.7508392 25.0739975 25.1092014 25.4164333 25.6675911 25.8876381 26.1953678 26.4954414 26.5988808 26.7599316 27.0222893 27.2829971 27.5116463 27.6182556 27.639101 27.6825905 27.6832371 27.9249477 27.9340248 28.1531639 28.3801289 28.5569229 28.5863419 28.9881287 29.129961 29.1764641 29.3689938 29.4900932 29.8110275 30.0332222 30.3447418 30.5119476 30.7667027 31.0793915 31.0934925 31.2368793 31.533783 31.8466854 31.9678535 32.0716553 32.1150131 32.35495 32.6314011 32.8635979 33.1323624 33.3543701 33.6157455 33.9106026 34.1764946 34.1801262 34.4203682 34.4224281 34.6706772 34.9539795 35.2678375 35.6259079 35.8609314 36.2931442 36.6264687 36.8469353 36.9730301 37.3091965 37.6073761 37.9847336 38.4823303 38.8703842 39.3720131 39.830368 40.1953049 40.4579277 40.5447044 41.0871811 41.6836891 42.3140755 43.2084961 43.8323898 44.9975586 45.9256516 45.9429016 46.9107666 49.0596466 50.7608948 50.7705688 54.9260826 86.3822861 ------------------------------ Transdef: Tab for variable 4 10.0008354 10.0235033 10.2009964 10.2837486 10.3762302 10.3774252 10.5277634 10.5748577 10.7282085 10.8268976 11.0011578 11.0834274 11.3006897 11.33078 11.4378223 11.4772663 11.6865578 11.7985497 12.0865822 12.3455391 12.5547724 12.8102665 12.9648256 13.2929974 13.3587666 13.4774027 13.5030651 13.6628704 13.8735676 13.8845482 13.9574299 14.0377493 14.0948277 14.268177 14.3770685 14.61693 14.9542656 15.1958065 15.2872648 15.4923649 15.853241 15.856843 16.0136929 16.3365021 16.5867615 16.6005363 16.9365959 17.1527176 17.5065384 17.9620018 18.2628345 18.4943562 18.609354 18.7535229 18.8141651 19.1625881 19.5557823 20.0010242 20.2177258 20.440834 20.6419258 20.813242 20.9974976 21.1524105 21.1629257 21.3171635 21.5267601 21.7046814 21.9338226 21.9339447 22.1600628 22.359787 22.7229385 23.0296688 23.1801872 23.3788834 23.5747623 23.8401489 24.1265182 24.3379269 24.6711235 25.0264969 25.2391777 25.5600147 25.952301 26.1957836 26.5177155 27.0172577 27.2547455 27.8479881 27.9282074 28.2364006 28.6657829 29.0664215 29.4257565 30.0889225 30.7597542 31.2624359 32.1325455 33.5792923 36.8028984 ------------------------------ Transdef: Tab for variable 5 2.35699153 3.06648636 3.06844378 3.41093564 3.62388277 3.78475332 3.94222307 4.18096352 4.19022703 4.35028887 4.56296158 4.59321451 4.65141678 4.68545818 4.7870636 4.91342115 5.04642773 5.13955879 5.14530468 5.15501451 5.25891209 5.27329922 5.36658573 5.46802855 5.54904652 5.65518951 5.71468019 5.81515884 5.85217905 5.96392632 6.07434177 6.15233421 6.17860031 6.21131897 6.26027298 6.33771324 6.33956957 6.39398003 6.4673748 6.48811245 6.52858734 6.5509758 6.57330084 6.63828278 6.65146923 6.70231056 6.77025986 6.82507229 6.82934189 6.86478329 6.93742657 6.96696758 6.9986105 7.04395199 7.11101532 7.16629887 7.22540426 7.24676657 7.27439117 7.29629993 7.31093073 7.3114233 7.36440945 7.40905571 7.42627907 7.48751688 7.54880714 7.60972118 7.61860657 7.67412663 7.69021797 7.73647308 7.78529882 7.82786655 7.84158993 7.88151455 7.94125271 7.99908495 8.06930161 8.13021755 8.20555305 8.27979851 8.36685181 8.41933823 8.47887897 8.50743675 8.58195305 8.67837143 8.76639557 8.86006355 8.96382999 9.07745361 9.22899818 9.3673439 9.54620934 9.73888683 10.0718021 10.3176928 10.7756338 11.4730091 14.2342319 ------------------------------ Transdef: Tab for variable 6 25.026516 27.1559372 27.2057476 28.5860786 28.7893105 29.3587189 29.701828 30.790741 31.2894974 31.6653385 31.8900146 32.927124 32.9654388 33.8431396 34.842659 35.0232124 35.7629509 36.4752808 37.0914841 37.8676529 37.9078674 38.5264587 39.1143646 39.7982864 39.8084259 40.2797775 40.3398056 40.4899559 41.1072693 41.9579964 42.0783691 42.557457 42.912365 43.0975189 43.7578735 43.8939972 44.6804924 45.3653183 45.9178276 46.5206604 46.8160133 47.0984573 47.5410461 47.9934998 48.120903 48.4929199 48.8811264 49.3891296 50.0126648 50.0667191 50.5189362 51.2188721 51.9124146 52.7252121 53.2421341 53.3128166 53.81567 54.2120781 54.2755051 54.7880402 55.6614227 56.1817627 56.7050705 56.9746513 57.0792198 57.7605286 58.6205826 59.2361832 60.0090523 60.6136932 61.1720047 62.237236 62.783493 63.6908646 64.5250702 65.3240128 66.0173798 66.8118286 67.5493011 68.3655701 69.2649841 69.5294342 70.1551437 71.3138657 72.2707672 73.0237579 73.8960342 75.3565063 76.3041153 77.5240479 79.1904297 80.6993408 83.8376617 86.9857635 88.6692276 90.9709015 95.1148071 100.928772 106.905602 118.030212 193.358276 ------------------------------ Transdef: Tab for variable 7 30.4153633 30.7424355 34.2097473 34.3271446 35.9225082 37.0269012 37.0686226 38.0262451 38.2110634 38.3035355 39.3953629 40.3705063 40.4002037 40.5778923 40.9671249 41.4962502 41.6136475 41.6185036 42.3635101 43.0842018 43.2587662 43.4916306 43.9189262 44.5932007 45.149189 45.1501503 45.466301 45.490078 46.3040771 47.1782227 47.6085701 48.2950935 49.1442337 49.9080124 50.5696945 51.2534103 52.0122147 52.6593475 53.0271301 53.3291969 54.0141373 54.9112625 55.835041 55.9653702 56.852356 57.695034 58.737175 59.4298706 60.0375748 60.6466103 61.3067513 61.6489372 62.3442192 63.1319122 63.8201256 64.0120392 64.8809662 65.5334167 66.4409637 67.1718597 67.9705658 68.8931046 69.8017273 70.5150146 71.477356 72.417244 73.3702545 73.4683533 74.5356827 75.5529022 76.8819046 78.3981171 78.6132507 79.6921158 81.3753662 81.9674606 82.6416321 84.3300629 85.7859955 87.0513153 88.9209747 90.223526 91.628685 91.6509171 92.6493835 94.5083847 96.4068451 98.4939423 99.6869507 101.763313 103.908546 108.181305 111.220474 115.510254 119.579605 124.972855 132.478973 137.302567 145.646042 167.335571 284.329834 ------------------------------ Transdef: Tab for variable 8 10.0344839 25.3657742 28.7567825 30.1748238 30.460907 32.1978378 32.9888611 33.5314102 33.8979568 34.6385498 35.3718529 36.1563416 36.4153976 36.6779404 36.8734055 37.1955948 37.3367615 37.9987946 38.0207825 38.5774422 38.7261162 39.3407402 39.8364029 40.4264297 40.5535507 40.8082657 41.1768379 41.3053131 41.6795959 41.8178024 42.0619736 42.0933113 42.096489 42.749752 43.3035164 43.6845512 43.8889236 44.1627808 44.2798424 44.2907257 44.3503342 44.8951607 45.3947525 46.0913811 46.4865265 46.998703 47.5260925 48.156601 48.5194664 49.0229187 49.5625076 50.1407509 50.5983925 51.0203552 51.5537338 51.9785538 52.4909668 53.0081863 53.1510582 53.7702637 53.8856583 54.3402328 55.1441498 55.6470642 56.4223442 57.212326 57.9109726 58.6244278 59.1286011 59.578701 60.3414841 60.8620644 61.501461 62.2128868 62.9929504 63.3964424 64.1970749 64.6877899 65.3538818 66.164711 67.02005 67.8904419 68.5590057 69.48172 70.9737244 71.8063507 73.010788 74.1360626 75.4235764 76.5061035 78.3703308 78.6135864 79.753479 81.9209213 84.6334686 88.3390808 91.9593506 98.5212173 103.823204 116.361664 200.177673 ------------------------------ Transdef: Tab for variable 9 56.5035744 61.4185257 67.2927475 68.3614502 68.6114044 70.1766663 70.2408142 71.9305496 71.9592896 74.3403473 75.5441589 78.0046082 78.7110062 79.6382904 79.7612381 80.6520996 81.0155945 81.3008423 81.8211136 83.4692383 84.5325241 84.5345917 84.746582 85.4396591 86.4692535 87.7012558 88.5262909 89.2147369 89.2397995 89.2848206 89.6543655 89.7342224 90.4174728 90.971283 91.6139221 91.8047562 91.9643707 92.6779785 93.0811157 93.4942932 94.5503616 95.6916809 96.4718781 97.3467865 98.8147964 100.011093 100.827545 101.48877 102.124611 102.13002 103.175751 103.99678 105.119583 105.940147 106.271088 106.438843 107.174919 107.815567 108.633652 109.312149 110.178238 110.179176 111.13179 112.108856 112.781242 113.822311 114.664352 115.681503 116.601021 118.037209 119.010475 119.992935 120.854919 121.583534 122.617813 124.068977 124.934219 126.364182 127.346596 128.383606 129.691193 130.543564 131.978653 133.174957 134.274689 135.66243 137.32547 138.348785 139.279266 140.535492 142.27034 144.494629 146.474854 148.139038 149.06575 151.345551 153.516541 156.376556 160.699799 170.248596 265.589417 ------------------------------ Transdef: Tab for variable 10 0.323437154 1.21547759 1.48516381 1.65926075 1.7899425 1.89352608 1.89764726 1.96122265 2.04981136 2.14778137 2.21537018 2.26290894 2.34137416 2.3904767 2.4292655 2.44297409 2.45383692 2.48578262 2.51181149 2.55031037 2.5831213 2.60846782 2.61862659 2.61894846 2.62636876 2.64950824 2.67076445 2.69228792 2.70650434 2.72822452 2.74167442 2.76029873 2.77353787 2.7767241 2.77892637 2.79799485 2.81577921 2.82903433 2.83991051 2.84252357 2.85704041 2.86729002 2.87211466 2.88196683 2.89292479 2.90420198 2.91065717 2.91711426 2.93319321 2.934026 2.94277668 2.94973207 2.95245838 2.96223116 2.96574354 2.97318268 2.97854042 2.98294783 2.99009562 2.99685431 3.00283647 3.00286674 3.01241112 3.0216856 3.02825332 3.02851009 3.0332489 3.03562284 3.03809738 3.04209566 3.04264069 3.04872084 3.05389071 3.05747724 3.06134748 3.067518 3.07184649 3.07871246 3.08349466 3.08350205 3.08578849 3.08986855 3.09482193 3.09660625 3.09835291 3.10188961 3.106143 3.10972857 3.10990191 3.11371446 3.11611533 3.11713886 3.12242627 3.1245532 3.12560844 3.12806606 3.13111973 3.13281679 3.13437581 3.13816762 3.14155698 ------------------------------ Transdef: Tab for variable 11 1.13248825E-05 0.00126773119 0.00448817015 0.0160882473 0.0356924534 0.0374727249 0.0447845459 0.0593456626 0.0706738383 0.0783894062 0.0881408751 0.0979610085 0.115702152 0.12640354 0.134966791 0.141909599 0.142059803 0.152767092 0.154354841 0.16118896 0.171859264 0.17337352 0.182694077 0.191077068 0.201950073 0.208353281 0.212662816 0.21347785 0.21969071 0.233430326 0.243151695 0.244357526 0.250965416 0.261245728 0.267953306 0.278905869 0.285778999 0.296219885 0.304572791 0.312406629 0.318484426 0.328620344 0.335366309 0.342040777 0.345094919 0.348023534 0.353433669 0.360956073 0.368594497 0.373598874 0.379913896 0.38565731 0.386790752 0.390664697 0.394408524 0.398491025 0.403211176 0.40786624 0.412739724 0.41753602 0.423074186 0.427813888 0.432751715 0.438029885 0.443581551 0.448426247 0.454105079 0.459609389 0.460082054 0.460250616 0.464981794 0.470888376 0.479907036 0.480054855 0.489154756 0.498427153 0.504851699 0.509507418 0.512559056 0.522607684 0.529923022 0.530429959 0.53441453 0.543285668 0.545382261 0.553675175 0.565267682 0.578988194 0.579622626 0.593021154 0.610030532 0.641142249 0.670770943 0.698834896 0.712153316 0.712675512 0.718458772 0.744321465 0.756315589 0.78678745 1.1301049 ------------------------------ Transdef: Tab for variable 12 0.200248539 0.223213226 0.229011357 0.255452454 0.278875113 0.315550357 0.336134493 0.348887265 0.40319562 0.405657738 0.408332229 0.411818802 0.414946914 0.418102562 0.420411885 0.420416623 0.423519552 0.425202429 0.428072393 0.430274814 0.43316704 0.435584664 0.43799445 0.440518439 0.443633229 0.446655482 0.450793862 0.45315659 0.456022829 0.457765698 0.46016562 0.462926984 0.466269851 0.469161749 0.471792996 0.474038303 0.477500737 0.480455458 0.484146804 0.486565679 0.489124715 0.492411554 0.4953022 0.49670732 0.501252472 0.504383028 0.507465363 0.509879827 0.51380527 0.516444921 0.517950714 0.519815743 0.523349285 0.526809275 0.530868888 0.535100043 0.538805246 0.542601109 0.54849273 0.54926008 0.551617086 0.552449286 0.557377338 0.559646428 0.5627985 0.567318439 0.572210431 0.57705164 0.577302456 0.580491126 0.584726214 0.588962197 0.595349312 0.601800442 0.609611332 0.616164148 0.62020278 0.626427293 0.634996533 0.643095016 0.655377746 0.660378993 0.666642427 0.675214291 0.688577533 0.692997217 0.698553801 0.699054003 0.708915949 0.714636147 0.725110769 0.725200176 0.745696783 0.748783827 0.769390643 0.769439638 0.771338284 0.790659904 0.834966779 0.872440696 1.13453126 ------------------------------ Transdef: Tab for variable 13 20.0277634 21.7915249 22.4360199 23.2636375 23.7460556 24.0863724 24.4333 24.9106693 24.9573746 25.1587982 25.3833694 25.8300209 26.3079395 26.8748837 27.0184517 27.3998756 27.6891441 27.7484226 28.1050873 28.4791622 28.8101006 28.8645916 29.0958233 29.2370071 29.4241333 29.4266586 29.6451817 29.7960281 29.9640388 30.2897873 30.4528236 30.77314 31.0515366 31.4039116 31.7479439 32.0554199 32.0568466 32.3485947 32.5592346 32.6829376 32.9288788 33.2526894 33.6010361 33.8045654 33.9357758 34.2867928 34.4429893 34.5406189 34.8443336 35.1889648 35.386116 35.5042 35.8292084 36.1878014 36.4124603 36.6864243 37.1843262 37.2562408 37.4127121 37.7556953 38.1278915 38.4938164 38.7570305 39.1642418 39.4749756 39.5912704 39.7760735 40.255619 40.7141953 41.0643196 41.4230156 42.0343666 42.4524612 42.6280365 42.8673286 43.3296127 43.5500336 43.968483 44.4598083 45.0551605 45.8416901 46.4290848 47.0935898 47.2925873 47.9369278 48.8369904 49.7830238 50.4614487 51.3285065 52.5548096 53.5982323 54.9316101 55.4284058 56.1314545 57.6103134 58.9381866 60.0053101 61.8946838 66.2778931 71.8053436 104.490562 ------------------------------ Transdef: Tab for variable 14 10.112442 10.5334015 10.5833817 10.583498 11.2144146 11.313796 11.481308 11.7955475 11.8485947 12.3023224 12.3030539 12.6822166 12.7744637 12.8190956 12.9634418 13.475647 13.4805012 13.6272535 13.7243862 14.1935692 14.5068665 14.7139025 15.1771975 15.4019718 15.5734081 16.0946407 16.3337975 16.435009 16.5978394 16.8075409 16.9561539 17.139082 17.1870079 17.5190029 18.0054417 18.250906 18.340023 18.74506 19.0790291 19.3461552 19.8160591 20.2125778 20.5387077 20.7408867 21.0156593 21.2646427 21.5835514 21.8443451 21.9334106 22.1171188 22.3607292 22.7054596 23.0232239 23.2650242 23.5487976 23.9393673 24.2931252 24.6353531 24.9001579 25.2477112 25.2727623 25.4720592 25.7936687 25.8116875 26.1050777 26.4023037 26.7003555 27.1094666 27.495985 27.7983246 28.1440125 28.5479698 28.94734 29.2867165 29.6175804 29.9473763 30.2490387 30.2884235 30.6608925 31.0918121 31.5433502 32.1292496 32.5595627 33.2170868 33.7073212 33.9888992 34.1213455 34.2193718 34.5804443 35.0646324 35.6997681 36.6805573 37.9765167 39.2246017 40.2134171 40.8170166 41.8730927 43.9002304 46.2643776 49.774929 65.4020844 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 48.8 17.4 41.7 21.4 37.3 44.5 40.4 46.0 -15.4 -9.3 -5.0 18.5 33.5 2 48.8 100.0 45.8 45.9 36.3 70.9 93.4 72.7 87.0 -42.5 -25.1 -26.6 44.4 40.7 3 17.4 45.8 100.0 17.8 6.1 24.4 47.6 37.0 55.7 -0.7 -24.0 -26.5 85.4 16.1 4 41.7 45.9 17.8 100.0 18.1 34.7 43.1 45.0 54.3 -1.4 -35.9 -50.9 23.4 82.3 5 21.4 36.3 6.1 18.1 100.0 85.7 2.7 57.0 66.9 27.8 -0.3 4.8 3.7 12.5 6 37.3 70.9 24.4 34.7 85.7 100.0 44.8 80.0 87.1 -0.2 -11.0 -7.6 21.8 28.9 7 44.5 93.4 47.6 43.1 2.7 44.8 100.0 59.8 69.4 -54.6 -27.6 -30.6 47.0 39.9 8 40.4 72.7 37.0 45.0 57.0 80.0 59.8 100.0 83.0 -2.6 -22.4 -23.5 36.0 39.2 9 46.0 87.0 55.7 54.3 66.9 87.1 69.4 83.0 100.0 -8.2 -24.9 -26.6 51.4 46.0 10 -15.4 -42.5 -0.7 -1.4 27.8 -0.2 -54.6 -2.6 -8.2 100.0 7.9 6.1 -1.3 -4.4 11 -9.3 -25.1 -24.0 -35.9 -0.3 -11.0 -27.6 -22.4 -24.9 7.9 100.0 55.2 -23.9 -37.4 12 -5.0 -26.6 -26.5 -50.9 4.8 -7.6 -30.6 -23.5 -26.6 6.1 55.2 100.0 -28.2 -41.1 13 18.5 44.4 85.4 23.4 3.7 21.8 47.0 36.0 51.4 -1.3 -23.9 -28.2 100.0 38.0 14 33.5 40.7 16.1 82.3 12.5 28.9 39.9 39.2 46.0 -4.4 -37.4 -41.1 38.0 100.0 TOTAL CORRELATION TO TARGET (diagonal) 117.52886 TOTAL CORRELATION OF ALL VARIABLES 57.8139062 ROUND 1: MAX CORR ( 57.8137042) AFTER KILLING INPUT VARIABLE 10 CONTR 0.152827695 ROUND 2: MAX CORR ( 57.8132888) AFTER KILLING INPUT VARIABLE 7 CONTR 0.219159457 ROUND 3: MAX CORR ( 57.812466) AFTER KILLING INPUT VARIABLE 11 CONTR 0.308435588 ROUND 4: MAX CORR ( 57.7839716) AFTER KILLING INPUT VARIABLE 3 CONTR 1.81489713 ROUND 5: MAX CORR ( 57.7133773) AFTER KILLING INPUT VARIABLE 6 CONTR 2.85542683 ROUND 6: MAX CORR ( 57.5168517) AFTER KILLING INPUT VARIABLE 5 CONTR 4.75874813 ROUND 7: MAX CORR ( 57.4582821) AFTER KILLING INPUT VARIABLE 13 CONTR 2.59500528 ROUND 8: MAX CORR ( 57.3188457) AFTER KILLING INPUT VARIABLE 9 CONTR 4.00051317 ROUND 9: MAX CORR ( 57.263615) AFTER KILLING INPUT VARIABLE 8 CONTR 2.51564612 ROUND 10: MAX CORR ( 57.1359051) AFTER KILLING INPUT VARIABLE 14 CONTR 3.82229665 ROUND 11: MAX CORR ( 53.4182665) AFTER KILLING INPUT VARIABLE 12 CONTR 20.2731462 ROUND 12: MAX CORR ( 48.7816702) AFTER KILLING INPUT VARIABLE 4 CONTR 21.7683219 LAST REMAINING VARIABLE: 2 total correlation to target: 57.8139062 % total significance: 28.0955484 sigma correlations of single variables to target: variable 2: 48.7816702 % , in sigma: 23.7061958 variable 3: 17.4054078 % , in sigma: 8.45842304 variable 4: 41.7133145 % , in sigma: 20.2712206 variable 5: 21.4230882 % , in sigma: 10.4108761 variable 6: 37.3385939 % , in sigma: 18.1452585 variable 7: 44.4617056 % , in sigma: 21.6068431 variable 8: 40.3559377 % , in sigma: 19.6115827 variable 9: 46.0361838 % , in sigma: 22.3719848 variable 10: -15.3634752 % , in sigma: 7.46611483 variable 11: -9.33921831 % , in sigma: 4.5385354 variable 12: -5.01859425 % , in sigma: 2.43886233 variable 13: 18.5137953 % , in sigma: 8.99706084 variable 14: 33.4863258 % , in sigma: 16.2731901 variables sorted by significance: 1 most relevant variable 2 corr 48.7816696 , in sigma: 23.7061954 2 most relevant variable 4 corr 21.768322 , in sigma: 10.5786477 3 most relevant variable 12 corr 20.2731457 , in sigma: 9.85204397 4 most relevant variable 14 corr 3.82229662 , in sigma: 1.85750327 5 most relevant variable 8 corr 2.51564622 , in sigma: 1.2225166 6 most relevant variable 9 corr 4.00051308 , in sigma: 1.94411027 7 most relevant variable 13 corr 2.59500527 , in sigma: 1.26108234 8 most relevant variable 5 corr 4.75874805 , in sigma: 2.31258611 9 most relevant variable 6 corr 2.85542679 , in sigma: 1.38763814 10 most relevant variable 3 corr 1.81489718 , in sigma: 0.881976931 11 most relevant variable 11 corr 0.308435589 , in sigma: 0.149888973 12 most relevant variable 7 corr 0.219159454 , in sigma: 0.106503875 13 most relevant variable 10 corr 0.152827695 , in sigma: 0.0742689464 global correlations between input variables: variable 2: 99.4389262 % variable 3: 94.7232911 % variable 4: 92.3054956 % variable 5: 98.1524664 % variable 6: 96.7904043 % variable 7: 99.3226254 % variable 8: 89.072762 % variable 9: 99.2317262 % variable 10: 74.0871473 % variable 11: 60.030558 % variable 12: 68.0407371 % variable 13: 91.4919446 % variable 14: 89.7685525 % significance loss when removing single variables: variable 2: corr = 6.30016478 % , sigma = 3.06166105 variable 3: corr = 1.76148831 % , sigma = 0.856022078 variable 4: corr = 19.8468262 % , sigma = 9.64486753 variable 5: corr = 4.47095078 % , sigma = 2.17272664 variable 6: corr = 2.71347907 % , sigma = 1.31865649 variable 7: corr = 0.204936783 % , sigma = 0.0995921517 variable 8: corr = 5.54796236 % , sigma = 2.69611682 variable 9: corr = 5.74592824 % , sigma = 2.79232136 variable 10: corr = 0.152827695 % , sigma = 0.0742689466 variable 11: corr = 0.293908209 % , sigma = 0.142829172 variable 12: corr = 18.6993358 % , sigma = 9.0872271 variable 13: corr = 2.58619964 % , sigma = 1.25680311 variable 14: corr = 4.45512679 % , sigma = 2.16503673 Keep only 3 most significant input variables ------------------------------------- Teacher: actual network topology: Nodes(1) = 4 Nodes(2) = 15 Nodes(3) = 1 ------------------------------------- --------------------------------------------------- Iteration : 1 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 10.4755983 sigma out 15 active outputs RANK 2 NODE 4 --> 9.70092678 sigma out 15 active outputs RANK 3 NODE 3 --> 8.20555401 sigma out 15 active outputs RANK 4 NODE 2 --> 4.61355877 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 11 --> 8.61880112 sigma in 4act. ( 12.4665365 sig out 1act.) RANK 2 NODE 9 --> 7.96020222 sigma in 4act. ( 8.69859982 sig out 1act.) RANK 3 NODE 12 --> 7.29016447 sigma in 4act. ( 7.75394535 sig out 1act.) RANK 4 NODE 4 --> 5.92692757 sigma in 4act. ( 6.84587049 sig out 1act.) RANK 5 NODE 13 --> 3.74751544 sigma in 4act. ( 3.38716054 sig out 1act.) RANK 6 NODE 1 --> 3.64734101 sigma in 4act. ( 3.60553789 sig out 1act.) RANK 7 NODE 14 --> 3.07986784 sigma in 4act. ( 3.32496381 sig out 1act.) RANK 8 NODE 15 --> 2.89416623 sigma in 4act. ( 3.01736116 sig out 1act.) RANK 9 NODE 8 --> 2.52709985 sigma in 4act. ( 2.42090464 sig out 1act.) RANK 10 NODE 5 --> 2.44062018 sigma in 4act. ( 2.51846218 sig out 1act.) RANK 11 NODE 7 --> 1.94491088 sigma in 4act. ( 1.9532398 sig out 1act.) RANK 12 NODE 6 --> 1.7481885 sigma in 4act. ( 2.01193309 sig out 1act.) RANK 13 NODE 10 --> 1.23327506 sigma in 4act. ( 1.31263924 sig out 1act.) RANK 14 NODE 3 --> 0.61550045 sigma in 4act. ( 0.0656291023 sig out 1act.) RANK 15 NODE 2 --> 0.498389065 sigma in 4act. ( 0.430898488 sig out 1act.) sorted by output significance RANK 1 NODE 11 --> 12.4665365 sigma out 1act.( 8.61880112 sig in 4act.) RANK 2 NODE 9 --> 8.69859982 sigma out 1act.( 7.96020222 sig in 4act.) RANK 3 NODE 12 --> 7.75394535 sigma out 1act.( 7.29016447 sig in 4act.) RANK 4 NODE 4 --> 6.84587049 sigma out 1act.( 5.92692757 sig in 4act.) RANK 5 NODE 1 --> 3.60553789 sigma out 1act.( 3.64734101 sig in 4act.) RANK 6 NODE 13 --> 3.38716054 sigma out 1act.( 3.74751544 sig in 4act.) RANK 7 NODE 14 --> 3.32496381 sigma out 1act.( 3.07986784 sig in 4act.) RANK 8 NODE 15 --> 3.01736116 sigma out 1act.( 2.89416623 sig in 4act.) RANK 9 NODE 5 --> 2.51846218 sigma out 1act.( 2.44062018 sig in 4act.) RANK 10 NODE 8 --> 2.42090464 sigma out 1act.( 2.52709985 sig in 4act.) RANK 11 NODE 6 --> 2.01193309 sigma out 1act.( 1.7481885 sig in 4act.) RANK 12 NODE 7 --> 1.9532398 sigma out 1act.( 1.94491088 sig in 4act.) RANK 13 NODE 10 --> 1.31263924 sigma out 1act.( 1.23327506 sig in 4act.) RANK 14 NODE 2 --> 0.430898488 sigma out 1act.( 0.498389065 sig in 4act.) RANK 15 NODE 3 --> 0.0656291023 sigma out 1act.( 0.61550045 sig in 4act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 20.1167049 sigma in 15 active inputs SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 11.7283411 sigma out 15 active outputs RANK 2 NODE 4 --> 11.5627775 sigma out 15 active outputs RANK 3 NODE 3 --> 9.58350468 sigma out 15 active outputs RANK 4 NODE 2 --> 8.19665909 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 11 --> 9.23744774 sigma in 4act. ( 9.79474545 sig out 1act.) RANK 2 NODE 9 --> 8.0604763 sigma in 4act. ( 8.11494064 sig out 1act.) RANK 3 NODE 12 --> 7.71912527 sigma in 4act. ( 7.83517408 sig out 1act.) RANK 4 NODE 4 --> 7.52282047 sigma in 4act. ( 5.68368292 sig out 1act.) RANK 5 NODE 1 --> 5.4859848 sigma in 4act. ( 4.0050869 sig out 1act.) RANK 6 NODE 6 --> 5.15861416 sigma in 4act. ( 3.10040522 sig out 1act.) RANK 7 NODE 5 --> 4.5087018 sigma in 4act. ( 2.99539781 sig out 1act.) RANK 8 NODE 2 --> 3.85095429 sigma in 4act. ( 1.95926273 sig out 1act.) RANK 9 NODE 7 --> 3.70459485 sigma in 4act. ( 2.18620539 sig out 1act.) RANK 10 NODE 14 --> 3.69394231 sigma in 4act. ( 2.88032317 sig out 1act.) RANK 11 NODE 13 --> 3.6774013 sigma in 4act. ( 2.07584953 sig out 1act.) RANK 12 NODE 8 --> 3.244977 sigma in 4act. ( 1.86101091 sig out 1act.) RANK 13 NODE 10 --> 2.91539574 sigma in 4act. ( 2.24866104 sig out 1act.) RANK 14 NODE 15 --> 2.51644564 sigma in 4act. ( 1.50736916 sig out 1act.) RANK 15 NODE 3 --> 2.38351631 sigma in 4act. ( 0.519288957 sig out 1act.) sorted by output significance RANK 1 NODE 11 --> 9.79474545 sigma out 1act.( 9.23744774 sig in 4act.) RANK 2 NODE 9 --> 8.11494064 sigma out 1act.( 8.0604763 sig in 4act.) RANK 3 NODE 12 --> 7.83517408 sigma out 1act.( 7.71912527 sig in 4act.) RANK 4 NODE 4 --> 5.68368292 sigma out 1act.( 7.52282047 sig in 4act.) RANK 5 NODE 1 --> 4.0050869 sigma out 1act.( 5.4859848 sig in 4act.) RANK 6 NODE 6 --> 3.10040522 sigma out 1act.( 5.15861416 sig in 4act.) RANK 7 NODE 5 --> 2.99539781 sigma out 1act.( 4.5087018 sig in 4act.) RANK 8 NODE 14 --> 2.88032317 sigma out 1act.( 3.69394231 sig in 4act.) RANK 9 NODE 10 --> 2.24866104 sigma out 1act.( 2.91539574 sig in 4act.) RANK 10 NODE 7 --> 2.18620539 sigma out 1act.( 3.70459485 sig in 4act.) RANK 11 NODE 13 --> 2.07584953 sigma out 1act.( 3.6774013 sig in 4act.) RANK 12 NODE 2 --> 1.95926273 sigma out 1act.( 3.85095429 sig in 4act.) RANK 13 NODE 8 --> 1.86101091 sigma out 1act.( 3.244977 sig in 4act.) RANK 14 NODE 15 --> 1.50736916 sigma out 1act.( 2.51644564 sig in 4act.) RANK 15 NODE 3 --> 0.519288957 sigma out 1act.( 2.38351631 sig in 4act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 17.9553452 sigma in 15 active inputs *********************************************** *** Learn Path 1 *** loss function: -0.42596969 *** contribution from regularisation: 0.0215895176 *** contribution from error: -0.447559208 *********************************************** -----------------> Test sample --------------------------------------------------- Iteration : 2 *********************************************** *** Learn Path 2 *** loss function: -0.487864316 *** contribution from regularisation: 0.0115144253 *** contribution from error: -0.499378741 *********************************************** -----------------> Test sample ENTER BFGS code START -2918.51451 -0.161894605 0.626974642 EXIT FROM BFGS code FG_START 0. -0.161894605 0. --------------------------------------------------- Iteration : 3 *********************************************** *** Learn Path 3 *** loss function: -0.499516606 *** contribution from regularisation: 0.00982315466 *** contribution from error: -0.50933975 *********************************************** -----------------> Test sample ENTER BFGS code FG_START -2987.60874 -0.161894605 -1.73534572 EXIT FROM BFGS code FG_LNSRCH 0. -0.172940493 0. --------------------------------------------------- Iteration : 4 *********************************************** *** Learn Path 4 *** loss function: -0.502263844 *** contribution from regularisation: 0.0139444564 *** contribution from error: -0.516208291 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3004.04014 -0.172940493 -6.6614418 EXIT FROM BFGS code NEW_X -3004.04014 -0.172940493 -6.6614418 ENTER BFGS code NEW_X -3004.04014 -0.172940493 -6.6614418 EXIT FROM BFGS code FG_LNSRCH 0. -0.182817861 0. --------------------------------------------------- Iteration : 5 *********************************************** *** Learn Path 5 *** loss function: -0.508688092 *** contribution from regularisation: 0.0120654469 *** contribution from error: -0.520753562 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3042.46337 -0.182817861 3.34850645 EXIT FROM BFGS code NEW_X -3042.46337 -0.182817861 3.34850645 ENTER BFGS code NEW_X -3042.46337 -0.182817861 3.34850645 EXIT FROM BFGS code FG_LNSRCH 0. -0.171586931 0. --------------------------------------------------- Iteration : 6 *********************************************** *** Learn Path 6 *** loss function: -0.509451807 *** contribution from regularisation: 0.0112325838 *** contribution from error: -0.520684361 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3047.03129 -0.171586931 2.07172251 EXIT FROM BFGS code NEW_X -3047.03129 -0.171586931 2.07172251 ENTER BFGS code NEW_X -3047.03129 -0.171586931 2.07172251 EXIT FROM BFGS code FG_LNSRCH 0. -0.151916087 0. --------------------------------------------------- Iteration : 7 *********************************************** *** Learn Path 7 *** loss function: -0.5095191 *** contribution from regularisation: 0.0111335432 *** contribution from error: -0.520652652 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3047.43367 -0.151916087 1.33852148 EXIT FROM BFGS code NEW_X -3047.43367 -0.151916087 1.33852148 ENTER BFGS code NEW_X -3047.43367 -0.151916087 1.33852148 EXIT FROM BFGS code FG_LNSRCH 0. -0.089724943 0. --------------------------------------------------- Iteration : 8 *********************************************** *** Learn Path 8 *** loss function: -0.511026025 *** contribution from regularisation: 0.00981716067 *** contribution from error: -0.520843208 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3056.44649 -0.089724943 -1.81323683 EXIT FROM BFGS code NEW_X -3056.44649 -0.089724943 -1.81323683 ENTER BFGS code NEW_X -3056.44649 -0.089724943 -1.81323683 EXIT FROM BFGS code FG_LNSRCH 0. -0.017562231 0. --------------------------------------------------- Iteration : 9 *********************************************** *** Learn Path 9 *** loss function: -0.510981441 *** contribution from regularisation: 0.0106770517 *** contribution from error: -0.52165848 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3056.17984 -0.017562231 -8.28816891 EXIT FROM BFGS code FG_LNSRCH 0. -0.0665958598 0. --------------------------------------------------- Iteration : 10 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 3 --> 9.98557091 sigma out 15 active outputs RANK 2 NODE 1 --> 8.17804718 sigma out 15 active outputs RANK 3 NODE 2 --> 7.64178705 sigma out 15 active outputs RANK 4 NODE 4 --> 6.3327179 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 12 --> 8.76249981 sigma in 4act. ( 8.49886227 sig out 1act.) RANK 2 NODE 6 --> 5.92532063 sigma in 4act. ( 4.60236549 sig out 1act.) RANK 3 NODE 2 --> 4.95508337 sigma in 4act. ( 3.84853745 sig out 1act.) RANK 4 NODE 1 --> 4.74235916 sigma in 4act. ( 3.38478518 sig out 1act.) RANK 5 NODE 11 --> 4.35573006 sigma in 4act. ( 3.39245963 sig out 1act.) RANK 6 NODE 5 --> 4.25509548 sigma in 4act. ( 2.86857414 sig out 1act.) RANK 7 NODE 9 --> 4.23225451 sigma in 4act. ( 3.14436626 sig out 1act.) RANK 8 NODE 4 --> 3.79346275 sigma in 4act. ( 1.33188808 sig out 1act.) RANK 9 NODE 10 --> 3.21835351 sigma in 4act. ( 2.14278531 sig out 1act.) RANK 10 NODE 7 --> 2.80769992 sigma in 4act. ( 1.54055238 sig out 1act.) RANK 11 NODE 3 --> 2.40019035 sigma in 4act. ( 1.50021815 sig out 1act.) RANK 12 NODE 8 --> 2.13181973 sigma in 4act. ( 1.80666423 sig out 1act.) RANK 13 NODE 13 --> 1.84516048 sigma in 4act. ( 0.144549996 sig out 1act.) RANK 14 NODE 14 --> 1.80637109 sigma in 4act. ( 0.365613043 sig out 1act.) RANK 15 NODE 15 --> 1.25058234 sigma in 4act. ( 0.627982974 sig out 1act.) sorted by output significance RANK 1 NODE 12 --> 8.49886227 sigma out 1act.( 8.76249981 sig in 4act.) RANK 2 NODE 6 --> 4.60236549 sigma out 1act.( 5.92532063 sig in 4act.) RANK 3 NODE 2 --> 3.84853745 sigma out 1act.( 4.95508337 sig in 4act.) RANK 4 NODE 11 --> 3.39245963 sigma out 1act.( 4.35573006 sig in 4act.) RANK 5 NODE 1 --> 3.38478518 sigma out 1act.( 4.74235916 sig in 4act.) RANK 6 NODE 9 --> 3.14436626 sigma out 1act.( 4.23225451 sig in 4act.) RANK 7 NODE 5 --> 2.86857414 sigma out 1act.( 4.25509548 sig in 4act.) RANK 8 NODE 10 --> 2.14278531 sigma out 1act.( 3.21835351 sig in 4act.) RANK 9 NODE 8 --> 1.80666423 sigma out 1act.( 2.13181973 sig in 4act.) RANK 10 NODE 7 --> 1.54055238 sigma out 1act.( 2.80769992 sig in 4act.) RANK 11 NODE 3 --> 1.50021815 sigma out 1act.( 2.40019035 sig in 4act.) RANK 12 NODE 4 --> 1.33188808 sigma out 1act.( 3.79346275 sig in 4act.) RANK 13 NODE 15 --> 0.627982974 sigma out 1act.( 1.25058234 sig in 4act.) RANK 14 NODE 14 --> 0.365613043 sigma out 1act.( 1.80637109 sig in 4act.) RANK 15 NODE 13 --> 0.144549996 sigma out 1act.( 1.84516048 sig in 4act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 12.8104382 sigma in 15 active inputs *********************************************** *** Learn Path 10 *** loss function: -0.507871389 *** contribution from regularisation: 0.0134929791 *** contribution from error: -0.521364391 *********************************************** -----------------> Test sample Iteration No: 10 ********************************************** ***** write out current network **** ***** to "rescue.nb" **** ********************************************** SAVING EXPERTISE TO rescue.nb ENTER BFGS code FG_LNSRCH -3037.57892 -0.0665958598 -3.05886507 EXIT FROM BFGS code FG_LNSRCH 0. -0.0886803865 0. --------------------------------------------------- Iteration : 11 *********************************************** *** Learn Path 11 *** loss function: -0.509690881 *** contribution from regularisation: 0.0111831976 *** contribution from error: -0.520874083 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3048.4612 -0.0886803865 -1.98631394 EXIT FROM BFGS code FG_LNSRCH 0. -0.0897188932 0. --------------------------------------------------- Iteration : 12 *********************************************** *** Learn Path 12 *** loss function: -0.510160625 *** contribution from regularisation: 0.0106826769 *** contribution from error: -0.520843327 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3051.27077 -0.0897188932 -1.96504736 EXIT FROM BFGS code FG_LNSRCH 0. -0.089724943 0. --------------------------------------------------- Iteration : 13 *********************************************** *** Learn Path 13 *** loss function: -0.51035881 *** contribution from regularisation: 0.0104843313 *** contribution from error: -0.520843148 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3052.45615 -0.089724943 -1.85038769 EXIT FROM BFGS code FG_LNSRCH 0. -0.089724943 0. --------------------------------------------------- Iteration : 14 *********************************************** *** Learn Path 14 *** loss function: -0.509016931 *** contribution from regularisation: 0.0118262069 *** contribution from error: -0.520843148 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3044.43039 -0.089724943 -2.00563622 EXIT FROM BFGS code FG_LNSRCH 0. -0.089724943 0. --------------------------------------------------- Iteration : 15 *********************************************** *** Learn Path 15 *** loss function: -0.510884821 *** contribution from regularisation: 0.00995832402 *** contribution from error: -0.520843148 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3055.6022 -0.089724943 -1.87785566 EXIT FROM BFGS code FG_LNSRCH 0. -0.089724943 0. --------------------------------------------------- Iteration : 16 *********************************************** *** Learn Path 16 *** loss function: -0.509379566 *** contribution from regularisation: 0.0114636216 *** contribution from error: -0.520843208 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3046.59901 -0.089724943 -1.95779335 EXIT FROM BFGS code NEW_X -3046.59901 -0.089724943 -1.95779335 ENTER BFGS code NEW_X -3046.59901 -0.089724943 -1.95779335 EXIT FROM BFGS code CONVERGENC -3046.59901 -0.089724943 -1.95779335 --------------------------------------------------- Iteration : 250 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 3 --> 11.0849266 sigma out 15 active outputs RANK 2 NODE 1 --> 9.49779224 sigma out 15 active outputs RANK 3 NODE 2 --> 7.79232407 sigma out 15 active outputs RANK 4 NODE 4 --> 7.493577 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 12 --> 10.2399502 sigma in 4act. ( 9.42887402 sig out 1act.) RANK 2 NODE 6 --> 6.41995239 sigma in 4act. ( 6.10549688 sig out 1act.) RANK 3 NODE 1 --> 5.56803846 sigma in 4act. ( 4.50107431 sig out 1act.) RANK 4 NODE 9 --> 5.35908985 sigma in 4act. ( 4.67514181 sig out 1act.) RANK 5 NODE 2 --> 5.22743654 sigma in 4act. ( 5.1806283 sig out 1act.) RANK 6 NODE 5 --> 4.91253853 sigma in 4act. ( 3.71167135 sig out 1act.) RANK 7 NODE 11 --> 4.80397797 sigma in 4act. ( 5.19417095 sig out 1act.) RANK 8 NODE 4 --> 3.62904978 sigma in 4act. ( 1.96333385 sig out 1act.) RANK 9 NODE 10 --> 3.39742112 sigma in 4act. ( 2.90551543 sig out 1act.) RANK 10 NODE 7 --> 2.89228654 sigma in 4act. ( 2.095083 sig out 1act.) RANK 11 NODE 3 --> 2.39323783 sigma in 4act. ( 1.92964959 sig out 1act.) RANK 12 NODE 8 --> 1.99890172 sigma in 4act. ( 1.82164705 sig out 1act.) RANK 13 NODE 13 --> 1.66707695 sigma in 4act. ( 0.00703765312 sig out 1act.) RANK 14 NODE 14 --> 1.66007841 sigma in 4act. ( 0.121607922 sig out 1act.) RANK 15 NODE 15 --> 1.13537371 sigma in 4act. ( 0.617830575 sig out 1act.) sorted by output significance RANK 1 NODE 12 --> 9.42887402 sigma out 1act.( 10.2399502 sig in 4act.) RANK 2 NODE 6 --> 6.10549688 sigma out 1act.( 6.41995239 sig in 4act.) RANK 3 NODE 11 --> 5.19417095 sigma out 1act.( 4.80397797 sig in 4act.) RANK 4 NODE 2 --> 5.1806283 sigma out 1act.( 5.22743654 sig in 4act.) RANK 5 NODE 9 --> 4.67514181 sigma out 1act.( 5.35908985 sig in 4act.) RANK 6 NODE 1 --> 4.50107431 sigma out 1act.( 5.56803846 sig in 4act.) RANK 7 NODE 5 --> 3.71167135 sigma out 1act.( 4.91253853 sig in 4act.) RANK 8 NODE 10 --> 2.90551543 sigma out 1act.( 3.39742112 sig in 4act.) RANK 9 NODE 7 --> 2.095083 sigma out 1act.( 2.89228654 sig in 4act.) RANK 10 NODE 4 --> 1.96333385 sigma out 1act.( 3.62904978 sig in 4act.) RANK 11 NODE 3 --> 1.92964959 sigma out 1act.( 2.39323783 sig in 4act.) RANK 12 NODE 8 --> 1.82164705 sigma out 1act.( 1.99890172 sig in 4act.) RANK 13 NODE 15 --> 0.617830575 sigma out 1act.( 1.13537371 sig in 4act.) RANK 14 NODE 14 --> 0.121607922 sigma out 1act.( 1.66007841 sig in 4act.) RANK 15 NODE 13 --> 0.00703765312 sigma out 1act.( 1.66707695 sig in 4act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 16.1250362 sigma in 15 active inputs *********************************************** *** Learn Path 250 *** loss function: -0.509957671 *** contribution from regularisation: 0.0108854771 *** contribution from error: -0.520843148 *********************************************** -----------------> Test sample END OF LEARNING , export EXPERTISE SAVING EXPERTISE TO expert.nb NB_AHISTOUT: storage space 22610 Closing output file done