NNInput NNInputs_185.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= 10761 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 = 1994 nbkg = 8767 Bkg Entries: 8767 Sig Entries: 1994 Chosen entries: 1994 Warning: entries low (below 6000) Signal fraction: 1 Background fraction: 0.227444 Signal Tree Copy Condition: Background Tree Copy Condition: Actual Background Entries: 8767 Actual Signal Entries: 1994 Entries to split: 1994 Test with : 997 Train with : 997 ********************************************* * 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= 1994 for Signal Prepared event 0 for Signal with 1994 events ====Entry 0 Variable Ht : 253.635 Variable LepAPt : 33.0747 Variable LepBPt : 20.1653 Variable MetSigLeptonsJets : 10.8476 Variable MetSpec : 123.667 Variable SumEtLeptonsJets : 129.968 Variable VSumJetLeptonsPt : 124.269 Variable addEt : 176.907 Variable dPhiLepSumMet : 2.88035 Variable dPhiLeptons : 0.451158 Variable dRLeptons : 0.595618 Variable lep1_E : 45.9485 Variable lep2_E : 22.4055 ===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 = 2185 Ht = 253.635 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 33.0749 LepAPt = 33.0747 LepBEt = 20.1657 LepBPt = 20.1653 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 123.667 MetDelPhi = 2.59919 MetSig = 8.57835 MetSigLeptonsJets = 10.8476 MetSpec = 123.667 Mjj = 0 MostCentralJetEta = 0.772112 MtllMet = 187.447 Njets = 1 SB = 0 SumEt = 207.825 SumEtJets = 0 SumEtLeptonsJets = 129.968 Target = 1 TrainWeight = 1 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 124.269 addEt = 176.907 dPhiLepSumMet = 2.88035 dPhiLeptons = 0.451158 dRLeptons = 0.595618 diltype = 41 dimass = 15.3522 event = 2717 jet1_Et = 76.7276 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 45.9485 lep2_E = 22.4055 rand = 0.999742 run = 235158 weight = 1.72963e-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 = 2.4656 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 291 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 10761 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 291 negative weights. Signal fraction: 66.9929352 % ------------------------------ 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 67.2503815 68.3159332 68.6018524 68.8894424 70.2056885 70.2088394 73.4231415 73.4309464 73.9544678 77.5021973 78.7032166 79.7862473 81.2808075 82.4259949 82.693634 83.4542694 84.5176544 86.1643982 86.2072906 88.0912476 88.5246582 89.2376251 89.2848206 89.3732224 91.025177 91.1699829 92.7673035 93.0962143 95.2734604 95.4649353 97.1569672 99.1192932 100.22657 100.591339 102.978645 104.99501 106.231461 106.434525 107.843506 109.293121 110.264969 110.81514 112.242477 113.014854 113.998329 115.892258 116.26442 116.879913 117.988159 119.547165 120.731339 120.992294 121.818275 123.449371 124.321068 125.142899 126.000687 127.106277 128.79776 130.06076 131.350586 132.964478 135.252228 137.319336 138.646759 140.251678 142.165329 143.624817 145.068207 146.653992 147.682541 148.147705 149.05072 150.742783 152.334045 154.977753 157.077606 159.393356 161.086151 162.549164 164.76593 166.061722 168.459015 170.521881 172.81546 175.65242 180.272461 183.754288 186.793854 190.390808 198.224701 204.672226 210.94426 218.9664 223.874069 236.385162 247.082733 267.70636 300.058319 454.126373 ------------------------------ Transdef: Tab for variable 3 20.0047188 20.4545612 20.9454269 21.4176712 21.5415344 21.6022968 21.974905 22.1419144 22.5586662 22.8598576 23.0430336 23.4908524 23.5897636 23.7405415 23.9124374 24.2643108 24.4978065 25.1050797 25.1100521 25.3879738 25.6719379 25.8532352 26.2577534 26.4281387 26.5831757 26.6033592 26.8802414 26.9472847 27.1256409 27.353981 27.6564789 27.6822891 27.8593521 27.9272861 28.1531639 28.2102489 28.5272789 28.9250317 29.1283245 29.1377583 29.1985073 29.5787582 29.9296646 30.4856377 30.5438805 30.7022648 30.9979362 31.0937042 31.3498383 31.4207268 31.5463676 31.8662453 31.9615517 32.2999306 32.7127838 33.2088623 33.2449036 33.4903717 33.7516861 34.0753555 34.1784821 34.4950104 34.8172836 35.1753387 35.611393 35.878067 36.2256317 36.6184082 36.8600349 37.2339325 37.5592957 37.5641212 38.0872231 38.0936432 38.5049133 39.022953 39.4097023 39.7335892 40.129631 40.7172089 41.2435379 41.9692421 42.4749908 43.1224442 43.6897087 44.3633118 45.0949631 45.7992096 46.3910294 47.0811234 48.3677368 49.6548347 50.7627258 51.0426407 52.804882 54.28685 56.0866547 58.045723 60.4314194 64.2168732 94.1731262 ------------------------------ Transdef: Tab for variable 4 10.0008354 10.177763 10.1972351 10.2849007 10.3762484 10.4499607 10.5278254 10.6644878 10.7585506 10.8260736 10.8840809 11.1152534 11.2996912 11.367259 11.3841448 11.4194298 11.5409184 11.7535744 11.8485765 12.187706 12.2005987 12.3537045 12.5279045 12.8675642 12.9482784 13.1902962 13.4767036 13.6851311 13.9521961 13.9771481 14.2898149 14.3778 14.6123333 14.909152 15.277956 15.2915459 15.4464874 15.4487724 15.7464256 16.1392422 16.4307976 16.435524 16.7571449 17.0913467 17.385437 17.6594753 17.8958244 18.1970806 18.4938278 18.495472 18.7535229 18.8191776 19.0669594 19.3386765 19.7005692 19.9985313 20.1756172 20.3958874 20.4069099 20.5824127 20.7745152 20.944109 21.0692978 21.1521072 21.1706104 21.2926178 21.4753418 21.7043018 21.8955116 21.9314098 22.0854645 22.3153152 22.4488239 22.6938438 22.9505348 23.2212505 23.4465923 23.6637535 23.9333439 24.1943398 24.5013123 24.9191208 25.1569881 25.4230614 25.6945953 26.0763474 26.1957836 26.4204273 26.6679306 27.1472282 27.5584145 27.8491707 27.9672318 28.4031563 28.9385071 29.6000557 30.7540512 31.57164 32.3400154 33.2884064 38.7876205 ------------------------------ Transdef: Tab for variable 5 2.3146708 3.06443143 3.25008202 3.3016367 3.41388416 3.78594947 3.7880106 3.95726681 4.17905807 4.38797474 4.5934453 4.62914658 4.75897598 4.81916332 4.96803474 5.09502268 5.13641405 5.15475178 5.18799591 5.31254101 5.41129589 5.56425381 5.68017006 5.70064926 5.81881618 5.82491493 5.83609724 5.92533016 6.0141573 6.02412939 6.10445309 6.10836554 6.18272495 6.21790695 6.23159504 6.25635576 6.27200508 6.27638817 6.35006762 6.4365716 6.48787546 6.52196503 6.55158329 6.61494923 6.6520071 6.66971636 6.75421429 6.82635403 6.83204889 6.87818527 6.96656513 6.98703718 7.03171778 7.09385014 7.16651821 7.21303749 7.25046921 7.3109827 7.34784031 7.40563107 7.42632246 7.46534729 7.51041985 7.55096149 7.61364985 7.6184454 7.69031286 7.69597912 7.76933098 7.81800652 7.84180641 7.88047743 7.95274782 8.0051918 8.06990433 8.13252258 8.21662903 8.27100468 8.32891083 8.40471458 8.4799881 8.53101349 8.5965004 8.64355659 8.7334156 8.81892776 8.91697693 8.993783 9.09052467 9.17710304 9.32600212 9.53198624 9.65115356 9.779356 9.94789505 10.1340647 10.3010559 10.524683 10.9153595 11.3895369 17.6174049 ------------------------------ Transdef: Tab for variable 6 25.0152855 26.7882919 27.0051575 27.2823639 29.2182941 29.3504333 31.2835484 31.4420605 31.9043064 32.7554131 32.96418 33.5753937 34.340744 34.7801247 35.9221649 35.9333839 35.9801331 36.4961205 36.5039711 37.4163475 37.4986572 37.8116608 37.8621445 38.1099014 39.1844711 39.5144043 40.2954712 40.3341293 40.4986763 41.4196129 41.9253845 42.6047859 42.9127121 43.0651474 43.7485123 43.9102097 44.836937 45.5251007 45.9229889 46.5203133 46.7559128 47.5437393 47.9477997 48.4714508 48.8724365 49.1410751 49.8710327 50.0485153 50.4195328 51.0117493 51.7029266 52.6360817 53.2370224 53.2444611 54.1148834 54.6978912 55.0711823 55.9925499 56.6099701 57.326107 58.2733574 59.0777435 59.5364914 60.0148926 60.7369423 61.5967331 62.3005142 63.2125397 64.0256195 64.5085831 65.0498276 65.6437073 66.8708191 67.8891449 68.5293274 69.2687683 69.5271301 69.6400757 71.111618 71.9302673 73.25737 74.4293365 75.6327515 76.9194794 78.158783 79.5119476 80.8475113 82.1633453 83.4809036 85.1004944 86.8322296 89.7353745 92.6323624 94.2577515 97.0231552 99.2853546 102.279205 104.921692 115.92823 124.552612 194.299576 ------------------------------ Transdef: Tab for variable 7 30.3449535 32.4570236 32.7929153 32.9081917 35.5715599 35.9282455 37.0503922 37.1731644 38.0176849 38.2110634 38.3035355 38.7281418 40.3915939 40.4015961 40.978508 41.6075516 41.6185036 41.9513397 42.083313 43.0314903 43.1219025 43.1749878 43.5877419 44.593544 45.0805664 45.473526 45.9706497 47.1800003 48.0065842 49.3084488 50.2389259 51.1914177 52.0799408 52.6255264 52.8845291 53.0271301 53.8741226 54.9359093 55.7552414 56.3463898 56.910759 57.3524857 58.1776123 58.7905502 59.1986008 60.0781593 61.0773659 61.6607475 62.70084 63.4112549 63.9887009 64.6263885 64.8877716 65.3454971 66.0662842 66.8929825 67.9002838 69.229538 70.1021271 71.3847656 72.1472168 72.1896896 73.7180786 74.5013199 75.9760208 77.3595734 78.1004791 78.5898056 78.9459534 79.8564301 81.3796387 81.9687119 82.5514984 83.3792572 85.4054184 87.2649307 88.2073975 89.8698273 91.2333679 91.6152496 93.2464142 93.7361145 95.2254486 96.7892151 98.3012695 100.222168 101.59343 104.75515 107.111092 110.22377 112.451797 116.904747 121.001526 125.805237 130.181305 136.985474 143.451797 154.472107 165.297134 186.555969 264.668427 ------------------------------ Transdef: Tab for variable 8 8.55078316 27.1006584 28.3040924 28.7937012 29.6773834 30.1428375 32.0121994 32.1027946 32.9818573 33.2801971 34.0553284 35.0089035 36.411499 36.4153976 36.6069946 36.8681068 36.8976059 37.3367615 37.3390045 38.0097733 38.0208931 39.1912727 40.0260696 40.4264297 40.8079758 41.2147293 41.3064079 41.464241 41.7627831 42.073185 42.1581459 42.6475601 42.7507782 43.1777077 43.7338791 44.1587067 44.2790451 44.5567017 45.2420273 45.3529587 45.9880943 46.7214966 47.4017792 48.0182419 48.9926605 49.6122284 50.2447472 50.8569412 51.0379105 51.5582161 52.0565109 52.6882706 53.0168304 53.2088242 53.8490791 54.2662201 54.9231033 55.3752823 55.8140297 56.2754707 56.9061317 57.3381119 58.0485458 58.635994 59.1347618 59.7491684 60.4737358 60.8833122 61.6881638 62.3610649 62.9066467 63.4652328 63.8680267 64.4937286 65.2395325 65.7447205 66.936142 68.0093842 68.9497528 69.8807983 70.619812 71.725647 72.9769897 74.22435 75.4353333 76.3612595 77.7101135 78.617012 78.628212 79.6562195 81.4771729 83.5496445 86.1159439 87.8797913 91.6364288 97.2174988 103.011505 110.52726 118.966751 127.038116 193.839172 ------------------------------ Transdef: Tab for variable 9 56.5035744 67.2503815 68.3159332 68.6018524 68.8892517 68.8894424 70.2088394 71.927948 72.3255997 73.4231415 73.9544678 74.5573578 76.972641 77.3756332 78.7110062 78.892868 79.7740021 80.2775726 81.3849869 82.4259949 82.687439 83.4542694 84.5272522 84.7221298 85.6421967 86.2072906 87.3377228 88.5262909 88.6566162 89.2376251 89.2854156 89.3442841 89.6733475 89.9878693 90.4212341 91.1138916 91.614418 92.588028 93.0962143 94.5229721 95.4044342 96.0692139 97.3917389 98.6113281 100.109367 100.993317 102.295853 103.350418 105.501373 106.231461 107.346146 108.201836 109.500412 110.229202 111.430367 112.314178 113.014854 113.821426 115.102829 116.183243 116.908089 117.940666 119.109711 120.523178 121.597717 122.757019 123.414703 124.163132 125.296318 126.001144 127.038071 127.914642 129.042969 130.201691 130.854645 131.760254 133.413239 134.579376 135.879913 137.424011 138.565842 139.480804 141.643814 142.876434 143.749771 145.221283 146.256775 148.139038 148.147705 150.07074 151.859039 154.470459 156.302307 158.932281 161.28241 163.613739 166.544327 171.032806 177.518494 184.466705 233.358902 ------------------------------ Transdef: Tab for variable 10 0.25151211 1.05746305 1.26485872 1.59883547 1.72326648 1.8947978 1.91782355 2.02932072 2.11188722 2.16698885 2.22183466 2.28207016 2.32600927 2.35082865 2.38085914 2.41050982 2.44171095 2.44320035 2.47273731 2.47922897 2.51432228 2.54991317 2.58392882 2.60343456 2.61236 2.6192615 2.63446045 2.6566782 2.68587255 2.71251965 2.72547841 2.74868584 2.7747581 2.77895093 2.78959155 2.81113529 2.82532644 2.83614826 2.83979106 2.84134674 2.84514809 2.86008787 2.86352634 2.8699398 2.8718853 2.88306904 2.89509559 2.89642143 2.90660429 2.91062498 2.91834545 2.93044424 2.93312025 2.93782616 2.94957209 2.95291901 2.96576452 2.96630764 2.97593784 2.97853637 2.98398209 2.98507118 2.98909712 2.99381876 3.0001018 3.00528693 3.01179242 3.01457715 3.01749086 3.02425671 3.02821016 3.03409362 3.04033136 3.04537058 3.05105448 3.0550952 3.0578413 3.0609889 3.06648636 3.06724882 3.07405543 3.07766342 3.08128548 3.08344007 3.08504272 3.0895083 3.09449363 3.09660101 3.09768724 3.10146165 3.10525894 3.10974336 3.11424732 3.11900353 3.12264919 3.12578201 3.12985229 3.13351393 3.13384771 3.137784 3.14155436 ------------------------------ Transdef: Tab for variable 11 1.13248825E-05 0.00141513348 0.00721523166 0.0222008228 0.0289435387 0.0374310315 0.0440593027 0.0549035072 0.0680191517 0.0813579559 0.0935093164 0.0975515544 0.109068662 0.120439887 0.131495416 0.142006934 0.146210909 0.155744076 0.163872808 0.172001362 0.173044145 0.181064487 0.197318316 0.212328121 0.213410378 0.218837023 0.226194561 0.234997854 0.240939856 0.244733274 0.251904249 0.261990547 0.267000735 0.268699855 0.273608685 0.27890873 0.280286074 0.28917262 0.303581357 0.309341252 0.314464569 0.318572521 0.325623512 0.330634117 0.338077784 0.34227547 0.345122337 0.349508941 0.351714075 0.356496155 0.362819135 0.367732823 0.376319706 0.381435454 0.386566579 0.391714603 0.400044441 0.404232442 0.409381449 0.414694726 0.421435833 0.425048292 0.426409006 0.430351198 0.435921669 0.437316954 0.44022727 0.444321811 0.451416969 0.459032536 0.460065484 0.463206083 0.472034574 0.473148108 0.479428053 0.480054855 0.486549586 0.492173761 0.495515615 0.506938934 0.514721513 0.522622228 0.523531437 0.525650859 0.534407735 0.536892414 0.549906135 0.559650183 0.579569042 0.593646169 0.620470405 0.649280906 0.680119276 0.712049007 0.712501824 0.714364052 0.755539179 0.78283447 0.86320442 0.883980572 1.11657131 ------------------------------ Transdef: Tab for variable 12 0.223213226 0.229011357 0.245130986 0.261999637 0.285422295 0.302297771 0.306726336 0.336134493 0.348887265 0.360201359 0.401258528 0.402652293 0.404316068 0.406240702 0.408533931 0.410559505 0.41273874 0.414296091 0.417529017 0.420075297 0.423161924 0.424747765 0.42636925 0.428897798 0.430046707 0.431056738 0.433306098 0.436651319 0.439423472 0.441344231 0.443708807 0.446561784 0.449563563 0.451830685 0.455671161 0.457182586 0.459274113 0.462456316 0.46541059 0.468254983 0.47178936 0.473675132 0.477722526 0.482089251 0.484711647 0.489316911 0.493097782 0.495288134 0.495654404 0.499655157 0.50059849 0.503285408 0.508433938 0.512912333 0.517630994 0.518046796 0.521051407 0.523650646 0.525969148 0.529767275 0.534676671 0.53815043 0.544213533 0.547894478 0.549279392 0.554136395 0.558673799 0.562438846 0.568188548 0.56850189 0.573204637 0.57728076 0.579874992 0.587080956 0.593173981 0.597884536 0.604112983 0.612918854 0.619719565 0.628084183 0.63410145 0.643769443 0.653393865 0.661746502 0.67160213 0.688116968 0.698481858 0.708755076 0.714663565 0.728647232 0.743054271 0.758061647 0.769390643 0.771338284 0.787183046 0.82762295 0.873316765 0.87531215 0.917575955 0.991762519 1.13453126 ------------------------------ Transdef: Tab for variable 13 20.0936413 21.7719135 22.2662125 23.1395073 23.7518826 24.0450287 24.4339485 24.5172539 24.9308262 25.1600475 25.5927162 26.2105865 26.7142181 27.0188484 27.3256569 27.3609505 27.6888733 27.9318924 28.4964008 28.8645916 28.8650169 29.2354164 29.2722054 29.4241333 29.6458054 30.312645 30.4475136 30.5591202 30.8677292 30.9187355 31.0635872 31.4131794 31.8462429 32.054863 32.206665 32.365303 32.4677582 32.7173843 33.1718025 33.4687805 33.6116447 33.8971634 34.2836304 34.6467743 34.725296 35.1720734 35.386116 35.614994 36.0445404 36.0811691 36.3280678 36.5201378 36.8551407 37.1711807 37.5198822 37.8162079 38.1278915 38.2219543 38.5526009 38.6090088 38.8255539 39.2685165 39.8051834 40.3047714 40.7384529 41.2120743 41.8266296 42.2758751 42.7595901 43.2243576 43.5500336 43.7933502 44.3714485 44.9282112 45.3861771 45.9680405 46.5928116 47.467762 48.4546967 49.3274879 50.1656952 50.7315826 52.0093002 53.2072906 54.2919502 55.2028618 55.5248985 56.3749275 57.3851128 58.4959259 58.9147415 59.3503571 60.58535 61.898922 63.2954674 66.543457 69.4183655 73.2874146 76.9982681 80.6404495 122.020348 ------------------------------ Transdef: Tab for variable 14 10.0521345 10.2623997 10.5334015 10.583498 10.8578959 10.8583193 11.2936745 11.3194752 11.3968935 11.725769 11.7810583 12.2148361 12.2997532 12.3871508 12.419363 12.9053907 13.2051907 13.3877773 13.475647 14.1443644 14.5075207 14.5972347 15.0194025 15.4054203 15.4184561 15.7283783 16.2390556 16.4728546 16.8049011 17.1111679 17.1864281 17.3730068 17.7398739 18.0229492 18.2740746 18.7584915 19.0772552 19.2133484 19.584095 19.9435806 20.348156 20.6615868 20.7408867 20.9024353 21.12854 21.3184566 21.4032135 21.6996155 21.9062767 21.9310246 22.2159576 22.5229034 22.7403984 23.0295563 23.3118858 23.5518761 23.7055397 23.8601723 24.0834579 24.5237579 24.9395771 25.2726936 25.5225601 25.7687302 26.0055237 26.2887917 26.6488914 27.0659065 27.4844208 27.7999802 28.2222958 28.5069122 28.7540131 29.1108932 29.4406853 30.1728172 30.2763214 30.6833115 31.3256798 31.6896591 32.226181 32.5419083 33.1733856 33.5945511 33.9866104 33.9905167 34.2171097 34.4841919 35.3965263 36.0739136 36.3865509 37.0792542 38.165184 39.6379051 40.2138481 40.4388618 42.6627579 45.1503983 47.7555618 48.9290466 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 56.4 31.8 38.0 34.0 47.7 50.4 50.6 55.5 -8.9 -11.8 2.2 29.4 28.8 2 56.4 100.0 54.0 44.2 42.5 71.3 93.9 75.6 89.6 -34.7 -30.6 -28.1 48.9 36.7 3 31.8 54.0 100.0 21.9 17.3 35.1 53.9 45.5 64.8 3.0 -32.2 -34.6 87.0 16.7 4 38.0 44.2 21.9 100.0 18.7 32.1 42.7 41.6 50.4 2.7 -33.0 -43.4 26.9 83.0 5 34.0 42.5 17.3 18.7 100.0 86.9 11.3 63.5 67.9 30.4 -6.0 8.4 10.8 10.0 6 47.7 71.3 35.1 32.1 86.9 100.0 47.1 82.9 85.5 7.3 -16.1 -4.6 27.4 21.6 7 50.4 93.9 53.9 42.7 11.3 47.1 100.0 62.6 74.2 -47.9 -33.7 -35.6 50.3 38.2 8 50.6 75.6 45.5 41.6 63.5 82.9 62.6 100.0 84.6 1.6 -27.6 -18.8 38.4 32.1 9 55.5 89.6 64.8 50.4 67.9 85.5 74.2 84.6 100.0 -4.1 -31.2 -25.9 57.1 39.8 10 -8.9 -34.7 3.0 2.7 30.4 7.3 -47.9 1.6 -4.1 100.0 4.6 6.4 -0.4 -3.1 11 -11.8 -30.6 -32.2 -33.0 -6.0 -16.1 -33.7 -27.6 -31.2 4.6 100.0 59.9 -31.6 -35.2 12 2.2 -28.1 -34.6 -43.4 8.4 -4.6 -35.6 -18.8 -25.9 6.4 59.9 100.0 -34.7 -37.6 13 29.4 48.9 87.0 26.9 10.8 27.4 50.3 38.4 57.1 -0.4 -31.6 -34.7 100.0 37.0 14 28.8 36.7 16.7 83.0 10.0 21.6 38.2 32.1 39.8 -3.1 -35.2 -37.6 37.0 100.0 TOTAL CORRELATION TO TARGET (diagonal) 138.457493 TOTAL CORRELATION OF ALL VARIABLES 66.4497279 ROUND 1: MAX CORR ( 66.4459108) AFTER KILLING INPUT VARIABLE 6 CONTR 0.712235321 ROUND 2: MAX CORR ( 66.4386142) AFTER KILLING INPUT VARIABLE 2 CONTR 0.984687225 ROUND 3: MAX CORR ( 66.3829457) AFTER KILLING INPUT VARIABLE 10 CONTR 2.71918683 ROUND 4: MAX CORR ( 66.2768035) AFTER KILLING INPUT VARIABLE 11 CONTR 3.75243811 ROUND 5: MAX CORR ( 66.1355923) AFTER KILLING INPUT VARIABLE 13 CONTR 4.32413125 ROUND 6: MAX CORR ( 66.0450741) AFTER KILLING INPUT VARIABLE 14 CONTR 3.45901252 ROUND 7: MAX CORR ( 65.8657355) AFTER KILLING INPUT VARIABLE 8 CONTR 4.86381535 ROUND 8: MAX CORR ( 65.0688109) AFTER KILLING INPUT VARIABLE 9 CONTR 10.2149378 ROUND 9: MAX CORR ( 64.4982417) AFTER KILLING INPUT VARIABLE 3 CONTR 8.59807967 ROUND 10: MAX CORR ( 61.126517) AFTER KILLING INPUT VARIABLE 5 CONTR 20.5808674 ROUND 11: MAX CORR ( 54.876382) AFTER KILLING INPUT VARIABLE 4 CONTR 26.9264511 ROUND 12: MAX CORR ( 50.4476458) AFTER KILLING INPUT VARIABLE 12 CONTR 21.5975078 LAST REMAINING VARIABLE: 7 total correlation to target: 66.4497279 % total significance: 25.402126 sigma correlations of single variables to target: variable 2: 56.3584086 % , in sigma: 21.5444584 variable 3: 31.8458449 % , in sigma: 12.1738973 variable 4: 37.9805722 % , in sigma: 14.5190554 variable 5: 34.0007728 % , in sigma: 12.9976742 variable 6: 47.7103525 % , in sigma: 18.2385154 variable 7: 50.4476458 % , in sigma: 19.2849165 variable 8: 50.6113573 % , in sigma: 19.3474995 variable 9: 55.4710019 % , in sigma: 21.2052242 variable 10: -8.92959458 % , in sigma: 3.41356833 variable 11: -11.8129801 % , in sigma: 4.51581696 variable 12: 2.23875058 % , in sigma: 0.855820274 variable 13: 29.4348222 % , in sigma: 11.2522216 variable 14: 28.8267898 % , in sigma: 11.0197855 variables sorted by significance: 1 most relevant variable 7 corr 50.4476471 , in sigma: 19.284917 2 most relevant variable 12 corr 21.5975075 , in sigma: 8.25620546 3 most relevant variable 4 corr 26.9264507 , in sigma: 10.2933318 4 most relevant variable 5 corr 20.5808678 , in sigma: 7.86756866 5 most relevant variable 3 corr 8.59807968 , in sigma: 3.28683819 6 most relevant variable 9 corr 10.2149382 , in sigma: 3.90492414 7 most relevant variable 8 corr 4.86381531 , in sigma: 1.85931912 8 most relevant variable 14 corr 3.45901251 , in sigma: 1.32229694 9 most relevant variable 13 corr 4.32413101 , in sigma: 1.65301084 10 most relevant variable 11 corr 3.75243807 , in sigma: 1.43446644 11 most relevant variable 10 corr 2.71918678 , in sigma: 1.03947943 12 most relevant variable 2 corr 0.984687209 , in sigma: 0.376422137 13 most relevant variable 6 corr 0.712235332 , in sigma: 0.272270365 global correlations between input variables: variable 2: 99.430194 % variable 3: 94.8623225 % variable 4: 90.1691954 % variable 5: 97.2063116 % variable 6: 95.9361754 % variable 7: 99.2269475 % variable 8: 89.9119217 % variable 9: 98.9117259 % variable 10: 72.3723208 % variable 11: 64.5172045 % variable 12: 69.5940476 % variable 13: 92.1916355 % variable 14: 90.0543408 % significance loss when removing single variables: variable 2: corr = 1.12197969 % , sigma = 0.428905735 variable 3: corr = 5.3032157 % , sigma = 2.02729127 variable 4: corr = 19.8242823 % , sigma = 7.5783443 variable 5: corr = 11.8137108 % , sigma = 4.5160963 variable 6: corr = 0.712235321 % , sigma = 0.272270361 variable 7: corr = 8.17552747 % , sigma = 3.12530669 variable 8: corr = 4.12223825 % , sigma = 1.57583212 variable 9: corr = 10.3756481 % , sigma = 3.96635965 variable 10: corr = 2.75488225 % , sigma = 1.05312495 variable 11: corr = 3.78419016 % , sigma = 1.4466045 variable 12: corr = 25.3827805 % , sigma = 9.7032239 variable 13: corr = 4.52501533 % , sigma = 1.72980407 variable 14: corr = 5.69518529 % , sigma = 2.17713178 Keep only 4 most significant input variables ------------------------------------- Teacher: actual network topology: Nodes(1) = 5 Nodes(2) = 15 Nodes(3) = 1 ------------------------------------- --------------------------------------------------- Iteration : 1 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 6.8035574 sigma out 15 active outputs RANK 2 NODE 2 --> 4.99213314 sigma out 15 active outputs RANK 3 NODE 3 --> 4.06084061 sigma out 15 active outputs RANK 4 NODE 4 --> 4.0348711 sigma out 15 active outputs RANK 5 NODE 5 --> 3.85436869 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 11 --> 5.34705448 sigma in 5act. ( 6.46885681 sig out 1act.) RANK 2 NODE 5 --> 4.8611784 sigma in 5act. ( 5.52284813 sig out 1act.) RANK 3 NODE 3 --> 4.78637075 sigma in 5act. ( 5.00355101 sig out 1act.) RANK 4 NODE 4 --> 3.533391 sigma in 5act. ( 3.33002281 sig out 1act.) RANK 5 NODE 13 --> 3.50401354 sigma in 5act. ( 3.91862655 sig out 1act.) RANK 6 NODE 14 --> 2.13506436 sigma in 5act. ( 2.12628627 sig out 1act.) RANK 7 NODE 7 --> 1.86780798 sigma in 5act. ( 1.94587743 sig out 1act.) RANK 8 NODE 6 --> 1.5731318 sigma in 5act. ( 1.79527915 sig out 1act.) RANK 9 NODE 10 --> 1.52280414 sigma in 5act. ( 1.6767782 sig out 1act.) RANK 10 NODE 15 --> 1.39235187 sigma in 5act. ( 1.37896502 sig out 1act.) RANK 11 NODE 2 --> 1.36830401 sigma in 5act. ( 1.58033204 sig out 1act.) RANK 12 NODE 8 --> 0.979348063 sigma in 5act. ( 0.783189774 sig out 1act.) RANK 13 NODE 12 --> 0.762763202 sigma in 5act. ( 0.596068978 sig out 1act.) RANK 14 NODE 1 --> 0.694318831 sigma in 5act. ( 0.363566577 sig out 1act.) RANK 15 NODE 9 --> 0.517108142 sigma in 5act. ( 0.499356627 sig out 1act.) sorted by output significance RANK 1 NODE 11 --> 6.46885681 sigma out 1act.( 5.34705448 sig in 5act.) RANK 2 NODE 5 --> 5.52284813 sigma out 1act.( 4.8611784 sig in 5act.) RANK 3 NODE 3 --> 5.00355101 sigma out 1act.( 4.78637075 sig in 5act.) RANK 4 NODE 13 --> 3.91862655 sigma out 1act.( 3.50401354 sig in 5act.) RANK 5 NODE 4 --> 3.33002281 sigma out 1act.( 3.533391 sig in 5act.) RANK 6 NODE 14 --> 2.12628627 sigma out 1act.( 2.13506436 sig in 5act.) RANK 7 NODE 7 --> 1.94587743 sigma out 1act.( 1.86780798 sig in 5act.) RANK 8 NODE 6 --> 1.79527915 sigma out 1act.( 1.5731318 sig in 5act.) RANK 9 NODE 10 --> 1.6767782 sigma out 1act.( 1.52280414 sig in 5act.) RANK 10 NODE 2 --> 1.58033204 sigma out 1act.( 1.36830401 sig in 5act.) RANK 11 NODE 15 --> 1.37896502 sigma out 1act.( 1.39235187 sig in 5act.) RANK 12 NODE 8 --> 0.783189774 sigma out 1act.( 0.979348063 sig in 5act.) RANK 13 NODE 12 --> 0.596068978 sigma out 1act.( 0.762763202 sig in 5act.) RANK 14 NODE 9 --> 0.499356627 sigma out 1act.( 0.517108142 sig in 5act.) RANK 15 NODE 1 --> 0.363566577 sigma out 1act.( 0.694318831 sig in 5act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 11.9966469 sigma in 15 active inputs SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 10.1816797 sigma out 15 active outputs RANK 2 NODE 2 --> 9.30473423 sigma out 15 active outputs RANK 3 NODE 3 --> 8.02590179 sigma out 15 active outputs RANK 4 NODE 5 --> 7.22833395 sigma out 15 active outputs RANK 5 NODE 4 --> 4.44539881 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 11 --> 8.02402592 sigma in 5act. ( 6.99287987 sig out 1act.) RANK 2 NODE 4 --> 7.0174818 sigma in 5act. ( 5.17926931 sig out 1act.) RANK 3 NODE 13 --> 6.38538361 sigma in 5act. ( 4.47681952 sig out 1act.) RANK 4 NODE 7 --> 5.59044266 sigma in 5act. ( 3.4455843 sig out 1act.) RANK 5 NODE 9 --> 5.28093863 sigma in 5act. ( 4.02038622 sig out 1act.) RANK 6 NODE 14 --> 4.86472654 sigma in 5act. ( 2.88610792 sig out 1act.) RANK 7 NODE 5 --> 4.70278835 sigma in 5act. ( 4.74068975 sig out 1act.) RANK 8 NODE 10 --> 4.02553844 sigma in 5act. ( 2.42181063 sig out 1act.) RANK 9 NODE 8 --> 3.38219047 sigma in 5act. ( 1.88650227 sig out 1act.) RANK 10 NODE 3 --> 3.35188842 sigma in 5act. ( 2.82091188 sig out 1act.) RANK 11 NODE 6 --> 3.05954003 sigma in 5act. ( 2.07685757 sig out 1act.) RANK 12 NODE 2 --> 2.69009972 sigma in 5act. ( 1.56291354 sig out 1act.) RANK 13 NODE 12 --> 2.68812966 sigma in 5act. ( 1.34282494 sig out 1act.) RANK 14 NODE 1 --> 1.56443298 sigma in 5act. ( 0.887022555 sig out 1act.) RANK 15 NODE 15 --> 1.48108256 sigma in 5act. ( 0.841817439 sig out 1act.) sorted by output significance RANK 1 NODE 11 --> 6.99287987 sigma out 1act.( 8.02402592 sig in 5act.) RANK 2 NODE 4 --> 5.17926931 sigma out 1act.( 7.0174818 sig in 5act.) RANK 3 NODE 5 --> 4.74068975 sigma out 1act.( 4.70278835 sig in 5act.) RANK 4 NODE 13 --> 4.47681952 sigma out 1act.( 6.38538361 sig in 5act.) RANK 5 NODE 9 --> 4.02038622 sigma out 1act.( 5.28093863 sig in 5act.) RANK 6 NODE 7 --> 3.4455843 sigma out 1act.( 5.59044266 sig in 5act.) RANK 7 NODE 14 --> 2.88610792 sigma out 1act.( 4.86472654 sig in 5act.) RANK 8 NODE 3 --> 2.82091188 sigma out 1act.( 3.35188842 sig in 5act.) RANK 9 NODE 10 --> 2.42181063 sigma out 1act.( 4.02553844 sig in 5act.) RANK 10 NODE 6 --> 2.07685757 sigma out 1act.( 3.05954003 sig in 5act.) RANK 11 NODE 8 --> 1.88650227 sigma out 1act.( 3.38219047 sig in 5act.) RANK 12 NODE 2 --> 1.56291354 sigma out 1act.( 2.69009972 sig in 5act.) RANK 13 NODE 12 --> 1.34282494 sigma out 1act.( 2.68812966 sig in 5act.) RANK 14 NODE 1 --> 0.887022555 sigma out 1act.( 1.56443298 sig in 5act.) RANK 15 NODE 15 --> 0.841817439 sigma out 1act.( 1.48108256 sig in 5act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 13.492321 sigma in 15 active inputs *********************************************** *** Learn Path 1 *** loss function: -0.505138099 *** contribution from regularisation: 0.0271832515 *** contribution from error: -0.532321334 *********************************************** -----------------> Test sample --------------------------------------------------- Iteration : 2 *********************************************** *** Learn Path 2 *** loss function: -0.572070897 *** contribution from regularisation: 0.00979277585 *** contribution from error: -0.581863701 *********************************************** -----------------> Test sample ENTER BFGS code START -3078.27947 -0.0973364934 -0.108981341 EXIT FROM BFGS code FG_START 0. -0.0973364934 0. --------------------------------------------------- Iteration : 3 *********************************************** *** Learn Path 3 *** loss function: -0.582128048 *** contribution from regularisation: 0.00603796449 *** contribution from error: -0.588165998 *********************************************** -----------------> Test sample ENTER BFGS code FG_START -3131.84893 -0.0973364934 -0.711177588 EXIT FROM BFGS code FG_LNSRCH 0. -0.11380627 0. --------------------------------------------------- Iteration : 4 *********************************************** *** Learn Path 4 *** loss function: -0.582243502 *** contribution from regularisation: 0.00982408598 *** contribution from error: -0.592067599 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3132.47019 -0.11380627 1.86376441 EXIT FROM BFGS code FG_LNSRCH 0. -0.105690539 0. --------------------------------------------------- Iteration : 5 *********************************************** *** Learn Path 5 *** loss function: -0.583177626 *** contribution from regularisation: 0.0103633823 *** contribution from error: -0.593541026 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3137.49573 -0.105690539 0.847608268 EXIT FROM BFGS code NEW_X -3137.49573 -0.105690539 0.847608268 ENTER BFGS code NEW_X -3137.49573 -0.105690539 0.847608268 EXIT FROM BFGS code FG_LNSRCH 0. -0.100326099 0. --------------------------------------------------- Iteration : 6 *********************************************** *** Learn Path 6 *** loss function: -0.583920896 *** contribution from regularisation: 0.00961496402 *** contribution from error: -0.593535841 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3141.49446 -0.100326099 0.182270676 EXIT FROM BFGS code NEW_X -3141.49446 -0.100326099 0.182270676 ENTER BFGS code NEW_X -3141.49446 -0.100326099 0.182270676 EXIT FROM BFGS code FG_LNSRCH 0. -0.0675164908 0. --------------------------------------------------- Iteration : 7 *********************************************** *** Learn Path 7 *** loss function: -0.569052756 *** contribution from regularisation: 0.00521699525 *** contribution from error: -0.574269772 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3061.50396 -0.0675164908 -9.41157818 EXIT FROM BFGS code FG_LNSRCH 0. -0.0976115838 0. --------------------------------------------------- Iteration : 8 *********************************************** *** Learn Path 8 *** loss function: -0.555257201 *** contribution from regularisation: 0.038121786 *** contribution from error: -0.593378961 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -2987.28382 -0.0976115838 -0.332803994 EXIT FROM BFGS code FG_LNSRCH 0. -0.100316264 0. --------------------------------------------------- Iteration : 9 *********************************************** *** Learn Path 9 *** loss function: -0.583753526 *** contribution from regularisation: 0.00978216715 *** contribution from error: -0.593535721 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3140.59392 -0.100316264 0.156696334 EXIT FROM BFGS code FG_LNSRCH 0. -0.100326076 0. --------------------------------------------------- Iteration : 10 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 3 --> 5.96654749 sigma out 15 active outputs RANK 2 NODE 1 --> 5.89848423 sigma out 15 active outputs RANK 3 NODE 5 --> 5.72517395 sigma out 15 active outputs RANK 4 NODE 2 --> 5.40212202 sigma out 15 active outputs RANK 5 NODE 4 --> 2.64835739 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 11 --> 4.7710433 sigma in 5act. ( 2.96228838 sig out 1act.) RANK 2 NODE 4 --> 4.63582325 sigma in 5act. ( 2.66479778 sig out 1act.) RANK 3 NODE 13 --> 4.27873993 sigma in 5act. ( 2.42764735 sig out 1act.) RANK 4 NODE 7 --> 4.04371691 sigma in 5act. ( 2.22024727 sig out 1act.) RANK 5 NODE 9 --> 3.9716208 sigma in 5act. ( 2.21903014 sig out 1act.) RANK 6 NODE 14 --> 3.31663966 sigma in 5act. ( 1.66894507 sig out 1act.) RANK 7 NODE 10 --> 2.85849094 sigma in 5act. ( 1.57045615 sig out 1act.) RANK 8 NODE 8 --> 2.33895874 sigma in 5act. ( 1.19628274 sig out 1act.) RANK 9 NODE 6 --> 2.23412538 sigma in 5act. ( 1.4458307 sig out 1act.) RANK 10 NODE 5 --> 2.20246196 sigma in 5act. ( 1.27499962 sig out 1act.) RANK 11 NODE 12 --> 1.87114573 sigma in 5act. ( 0.949405253 sig out 1act.) RANK 12 NODE 2 --> 1.78616095 sigma in 5act. ( 0.969023705 sig out 1act.) RANK 13 NODE 3 --> 1.2390914 sigma in 5act. ( 0.371501088 sig out 1act.) RANK 14 NODE 1 --> 1.08881021 sigma in 5act. ( 0.571848571 sig out 1act.) RANK 15 NODE 15 --> 0.884892821 sigma in 5act. ( 0.449624211 sig out 1act.) sorted by output significance RANK 1 NODE 11 --> 2.96228838 sigma out 1act.( 4.7710433 sig in 5act.) RANK 2 NODE 4 --> 2.66479778 sigma out 1act.( 4.63582325 sig in 5act.) RANK 3 NODE 13 --> 2.42764735 sigma out 1act.( 4.27873993 sig in 5act.) RANK 4 NODE 7 --> 2.22024727 sigma out 1act.( 4.04371691 sig in 5act.) RANK 5 NODE 9 --> 2.21903014 sigma out 1act.( 3.9716208 sig in 5act.) RANK 6 NODE 14 --> 1.66894507 sigma out 1act.( 3.31663966 sig in 5act.) RANK 7 NODE 10 --> 1.57045615 sigma out 1act.( 2.85849094 sig in 5act.) RANK 8 NODE 6 --> 1.4458307 sigma out 1act.( 2.23412538 sig in 5act.) RANK 9 NODE 5 --> 1.27499962 sigma out 1act.( 2.20246196 sig in 5act.) RANK 10 NODE 8 --> 1.19628274 sigma out 1act.( 2.33895874 sig in 5act.) RANK 11 NODE 2 --> 0.969023705 sigma out 1act.( 1.78616095 sig in 5act.) RANK 12 NODE 12 --> 0.949405253 sigma out 1act.( 1.87114573 sig in 5act.) RANK 13 NODE 1 --> 0.571848571 sigma out 1act.( 1.08881021 sig in 5act.) RANK 14 NODE 15 --> 0.449624211 sigma out 1act.( 0.884892821 sig in 5act.) RANK 15 NODE 3 --> 0.371501088 sigma out 1act.( 1.2390914 sig in 5act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 6.67306423 sigma in 15 active inputs *********************************************** *** Learn Path 10 *** loss function: -0.583180189 *** contribution from regularisation: 0.0103556653 *** contribution from error: -0.593535841 *********************************************** -----------------> Test sample Iteration No: 10 ********************************************** ***** write out current network **** ***** to "rescue.nb" **** ********************************************** SAVING EXPERTISE TO rescue.nb ENTER BFGS code FG_LNSRCH -3137.50948 -0.100326076 0.149840876 EXIT FROM BFGS code FG_LNSRCH 0. -0.100326099 0. --------------------------------------------------- Iteration : 11 *********************************************** *** Learn Path 11 *** loss function: -0.584102333 *** contribution from regularisation: 0.0094335191 *** contribution from error: -0.593535841 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3142.47063 -0.100326099 0.208593845 EXIT FROM BFGS code FG_LNSRCH 0. -0.100326099 0. --------------------------------------------------- Iteration : 12 *********************************************** *** Learn Path 12 *** loss function: -0.58315295 *** contribution from regularisation: 0.0103829447 *** contribution from error: -0.5935359 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3137.36272 -0.100326099 0.198634073 EXIT FROM BFGS code FG_LNSRCH 0. -0.100326099 0. --------------------------------------------------- Iteration : 13 *********************************************** *** Learn Path 13 *** loss function: -0.583159685 *** contribution from regularisation: 0.0103761917 *** contribution from error: -0.5935359 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3137.39905 -0.100326099 0.21484302 EXIT FROM BFGS code NEW_X -3137.39905 -0.100326099 0.21484302 ENTER BFGS code NEW_X -3137.39905 -0.100326099 0.21484302 EXIT FROM BFGS code CONVERGENC -3137.39905 -0.100326099 0.21484302 --------------------------------------------------- Iteration : 250 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 3 --> 9.60502338 sigma out 15 active outputs RANK 2 NODE 1 --> 9.52729416 sigma out 15 active outputs RANK 3 NODE 2 --> 7.50601339 sigma out 15 active outputs RANK 4 NODE 5 --> 6.81551504 sigma out 15 active outputs RANK 5 NODE 4 --> 3.77314448 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 11 --> 7.31052876 sigma in 5act. ( 5.81618071 sig out 1act.) RANK 2 NODE 4 --> 7.27231359 sigma in 5act. ( 4.39618254 sig out 1act.) RANK 3 NODE 13 --> 6.2738061 sigma in 5act. ( 4.13869047 sig out 1act.) RANK 4 NODE 9 --> 6.21286583 sigma in 5act. ( 4.05488682 sig out 1act.) RANK 5 NODE 7 --> 6.06628084 sigma in 5act. ( 3.94857478 sig out 1act.) RANK 6 NODE 14 --> 4.70438051 sigma in 5act. ( 2.99075007 sig out 1act.) RANK 7 NODE 10 --> 3.92144847 sigma in 5act. ( 2.33427477 sig out 1act.) RANK 8 NODE 8 --> 3.21746063 sigma in 5act. ( 1.99809039 sig out 1act.) RANK 9 NODE 6 --> 2.93048239 sigma in 5act. ( 2.2783792 sig out 1act.) RANK 10 NODE 5 --> 2.73019338 sigma in 5act. ( 2.21302414 sig out 1act.) RANK 11 NODE 12 --> 2.45293713 sigma in 5act. ( 1.47032261 sig out 1act.) RANK 12 NODE 2 --> 2.16900682 sigma in 5act. ( 1.35171318 sig out 1act.) RANK 13 NODE 3 --> 1.30904233 sigma in 5act. ( 0.533879995 sig out 1act.) RANK 14 NODE 1 --> 1.27737856 sigma in 5act. ( 0.75813061 sig out 1act.) RANK 15 NODE 15 --> 0.996979833 sigma in 5act. ( 0.633828282 sig out 1act.) sorted by output significance RANK 1 NODE 11 --> 5.81618071 sigma out 1act.( 7.31052876 sig in 5act.) RANK 2 NODE 4 --> 4.39618254 sigma out 1act.( 7.27231359 sig in 5act.) RANK 3 NODE 13 --> 4.13869047 sigma out 1act.( 6.2738061 sig in 5act.) RANK 4 NODE 9 --> 4.05488682 sigma out 1act.( 6.21286583 sig in 5act.) RANK 5 NODE 7 --> 3.94857478 sigma out 1act.( 6.06628084 sig in 5act.) RANK 6 NODE 14 --> 2.99075007 sigma out 1act.( 4.70438051 sig in 5act.) RANK 7 NODE 10 --> 2.33427477 sigma out 1act.( 3.92144847 sig in 5act.) RANK 8 NODE 6 --> 2.2783792 sigma out 1act.( 2.93048239 sig in 5act.) RANK 9 NODE 5 --> 2.21302414 sigma out 1act.( 2.73019338 sig in 5act.) RANK 10 NODE 8 --> 1.99809039 sigma out 1act.( 3.21746063 sig in 5act.) RANK 11 NODE 12 --> 1.47032261 sigma out 1act.( 2.45293713 sig in 5act.) RANK 12 NODE 2 --> 1.35171318 sigma out 1act.( 2.16900682 sig in 5act.) RANK 13 NODE 1 --> 0.75813061 sigma out 1act.( 1.27737856 sig in 5act.) RANK 14 NODE 15 --> 0.633828282 sigma out 1act.( 0.996979833 sig in 5act.) RANK 15 NODE 3 --> 0.533879995 sigma out 1act.( 1.30904233 sig in 5act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 11.6636724 sigma in 15 active inputs *********************************************** *** Learn Path 250 *** loss function: -0.582341015 *** contribution from regularisation: 0.0111948717 *** contribution from error: -0.5935359 *********************************************** -----------------> Test sample END OF LEARNING , export EXPERTISE SAVING EXPERTISE TO expert.nb NB_AHISTOUT: storage space 23090 Closing output file done