NNInput NNInputs_145.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= 11952 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 = 3185 nbkg = 8767 Bkg Entries: 8767 Sig Entries: 3185 Chosen entries: 3185 Warning: entries low (below 6000) Signal fraction: 1 Background fraction: 0.363294 Signal Tree Copy Condition: Background Tree Copy Condition: Actual Background Entries: 8767 Actual Signal Entries: 3185 Entries to split: 3185 Test with : 1592 Train with : 1592 ********************************************* * 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= 3185 for Signal Prepared event 0 for Signal with 3185 events ====Entry 0 Variable Ht : 149.137 Variable LepAPt : 28.178 Variable LepBPt : 23.4539 Variable MetSigLeptonsJets : 7.13581 Variable MetSpec : 65.3267 Variable SumEtLeptonsJets : 83.8097 Variable VSumJetLeptonsPt : 81.9577 Variable addEt : 116.959 Variable dPhiLepSumMet : 2.64655 Variable dPhiLeptons : 0.533672 Variable dRLeptons : 0.611018 Variable lep1_E : 39.2979 Variable lep2_E : 41.0529 ===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 = 2145 Ht = 149.137 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 28.1781 LepAPt = 28.178 LepBEt = 23.4541 LepBPt = 23.4539 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 65.3267 MetDelPhi = 2.35471 MetSig = 5.20626 MetSigLeptonsJets = 7.13581 MetSpec = 65.3267 Mjj = 0 MostCentralJetEta = 1.71926 MtllMet = 132.252 Njets = 1 SB = 0 SumEt = 157.445 SumEtJets = 0 SumEtLeptonsJets = 83.8097 Target = 1 TrainWeight = 1 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 81.9577 addEt = 116.959 dPhiLepSumMet = 2.64655 dPhiLeptons = 0.533672 dRLeptons = 0.611018 diltype = 43 dimass = 15.5828 event = 40 jet1_Et = 32.1778 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 39.2979 lep2_E = 41.0529 rand = 0.999742 run = 236524 weight = 2.93189e-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 = 4.05741 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 297 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 11952 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 297 negative weights. Signal fraction: 67.4262161 % ------------------------------ 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 61.3395729 67.2503815 68.8892517 70.2539062 73.3969879 74.4365921 75.0875549 77.8303986 80.0084991 80.6521149 82.0089188 82.4259949 82.6911774 84.0443268 86.0343628 86.2084045 87.5115509 88.5266266 89.1505585 89.2325592 90.6569672 91.0899658 91.9674072 92.0606689 93.7665558 94.9627304 95.2896957 95.6014862 95.8049927 96.6363831 97.142128 97.2838669 98.8595123 100.219727 100.52372 101.723495 102.575676 104.060455 105.426743 106.263771 106.513992 107.772659 108.807083 109.199554 109.750824 110.798836 110.876038 111.921265 113.041107 114.184174 115.251953 116.125832 117.154144 118.580605 119.834351 120.93428 121.005203 121.994469 123.033142 124.01722 125.23439 125.46283 126.633896 127.591217 128.378754 128.512222 129.817017 131.213638 132.452209 134.052429 135.576508 136.538361 138.731384 140.324432 141.928497 143.361298 145.768326 147.823639 148.13121 149.529419 151.760803 153.320618 154.456451 156.268219 158.729416 160.403625 163.956528 167.395172 170.187851 173.496552 177.019623 180.785461 184.863144 188.905518 197.770538 205.60434 214.423218 242.831955 287.594604 768.217102 ------------------------------ Transdef: Tab for variable 3 20.0047188 20.1094894 20.4820366 20.9005623 21.4175529 21.4190178 21.8207588 22.0091763 22.1471405 22.3305511 22.5842533 22.9847908 23.4589405 23.7506065 23.9127331 24.083437 24.3403206 24.7219791 25.1125336 25.52388 25.8028107 26.0845299 26.2907791 26.4299679 26.5150909 26.6016521 26.683403 26.9534283 27.0723763 27.291378 27.5788994 27.7646446 27.969429 28.154438 28.2732315 28.5025024 28.556778 28.7295494 29.043539 29.1369057 29.3008862 29.3684425 29.4958687 29.7796497 30.0278282 30.2641449 30.4364166 30.7848377 30.9640312 31.0006695 31.0936775 31.1605568 31.4207268 31.4983788 31.6794777 31.9155655 32.1179886 32.1641884 32.4615555 32.7378769 33.0554924 33.2348633 33.325695 33.5890121 33.8435555 34.1060486 34.176651 34.3707581 34.5800247 34.9191284 35.2394638 35.5398598 35.9052658 36.367836 36.6756287 37.099987 37.475544 37.5641212 37.782608 38.0922546 38.0939598 38.4781265 38.9921951 39.4300766 39.8539696 40.4525223 40.4619789 41.0116882 41.7145729 41.7646408 42.7478867 43.5139618 44.4466133 45.511879 46.4668198 48.0430374 49.8254623 50.7534027 52.813385 57.0545807 89.2475891 ------------------------------ Transdef: Tab for variable 4 10.0011806 10.1743135 10.1795731 10.3762302 10.4586315 10.561121 10.7576504 10.7860384 10.9642868 10.9990463 11.2038288 11.2993736 11.3841448 11.4045935 11.6343746 11.6857738 11.7535744 11.9140434 12.1734467 12.3886528 12.6509686 12.6544771 12.8232174 12.9481421 13.1023436 13.3208847 13.3589077 13.5982323 13.9077587 14.1005878 14.1187057 14.1804562 14.3406506 14.3795662 14.6148615 14.9277039 15.2914362 15.4308567 15.4483528 15.7073498 15.9543495 16.3303013 16.4360771 16.5916233 16.5918274 16.7316933 16.8351021 17.1551857 17.5303307 17.8904457 18.1725349 18.4078445 18.6264114 18.8986168 19.1270142 19.3416138 19.5637951 19.8591766 20.055315 20.2569408 20.3992348 20.4074993 20.5818596 20.8067646 21.0256329 21.1521072 21.2083435 21.3781033 21.6690388 21.8419037 21.9339447 21.9897003 22.1511803 22.4015121 22.5973396 22.8119698 23.0523777 23.3256836 23.6955643 23.9756145 24.2197132 24.6107502 24.9700241 25.2508278 25.461235 25.7275009 26.1189957 26.1941223 26.3259735 26.6134491 27.0600185 27.3736248 27.8386974 27.8491707 28.3457031 28.9848461 29.6907845 30.7289543 31.5806198 33.0289993 37.3070869 ------------------------------ Transdef: Tab for variable 5 2.3146708 3.06443143 3.17600536 3.25259066 3.30318403 3.46699882 3.69159698 3.96215439 4.18096352 4.1832943 4.31854534 4.47916126 4.5929184 4.62914658 4.62917376 4.65141678 4.70342684 4.70686436 4.75972986 4.80275679 4.95951939 5.09940815 5.1768074 5.30089426 5.46453619 5.58467293 5.67263889 5.70110893 5.744133 5.82491493 5.90540886 5.95178986 6.01415014 6.04274893 6.12323952 6.20007658 6.21729708 6.26230764 6.27200508 6.27638817 6.33440542 6.3396244 6.38884115 6.45371532 6.48787546 6.51034737 6.55644608 6.63268757 6.69718742 6.72960424 6.74005699 6.81908607 6.86711502 6.92560339 6.96646309 6.96725941 6.96736813 7.02289963 7.06440258 7.14000988 7.19816875 7.23840618 7.27691269 7.3114233 7.32117176 7.37398577 7.42658567 7.42688751 7.48427629 7.50128651 7.53000927 7.59284401 7.64273548 7.70321083 7.74836254 7.8149538 7.84180641 7.85753632 7.91753197 7.97021914 8.04657936 8.10567665 8.17311096 8.27682972 8.33677197 8.40548134 8.45867157 8.5059166 8.56881523 8.67403603 8.76246262 8.87550449 9.00231075 9.09894753 9.23784542 9.38516617 9.64807129 9.82082176 10.2416115 11.0593033 16.9851913 ------------------------------ Transdef: Tab for variable 6 25.0229874 27.0051575 27.0059814 27.2089481 27.2810001 28.3940544 28.8051319 29.3471088 29.4311829 30.6693344 31.8920517 32.9351425 33.5818596 33.8050842 34.7474899 34.8483429 35.9224396 35.9779587 36.4807129 36.4961205 36.7468185 37.5614319 37.8684387 38.0718155 38.9768906 39.5144043 39.9412041 40.280571 40.3395119 40.4851341 41.0976753 41.800972 42.6443863 43.3432312 43.757782 44.1719055 44.8468323 45.4566116 45.9243546 46.2933502 46.5205612 46.816246 46.8164062 47.5208778 47.5437393 48.0763474 48.4554443 49.1499062 49.6254501 50.1398773 50.4211807 50.4227028 51.1584396 51.906971 52.4181747 53.1654587 53.2332726 53.5404739 54.122963 54.4682388 55.121582 55.6314392 56.4125595 56.8717575 56.8960762 57.3057632 57.8941727 58.7828712 59.2918434 60.0318947 60.5833511 61.1617355 61.6644478 62.4059296 63.005394 63.4783478 63.9368858 64.7682953 65.5451355 66.3113556 67.019104 67.6094666 68.4732208 69.4377289 69.5303574 70.0487976 70.9392395 71.882576 73.0084076 74.1255188 75.3914185 76.670166 78.0743256 80.090683 82.1363907 84.7924347 88.1695938 91.8731537 96.5728073 108.636147 204.806641 ------------------------------ Transdef: Tab for variable 7 30.1901207 32.8785172 33.789772 34.215313 35.4913597 36.5672112 36.7645683 38.0262604 38.9624023 40.1918793 40.3705063 40.6647949 40.9810867 41.499958 42.0852432 42.4688644 43.1740952 43.772583 44.590107 44.6310959 45.1500931 45.1501236 45.1774521 45.466301 45.9180107 46.5583 47.3567734 48.0169907 48.945015 49.500988 50.1903648 50.9108467 51.6037254 52.2312279 52.6259613 53.0009537 53.0271301 53.4095535 53.9664536 54.7786865 55.3872986 55.9625549 56.5275497 57.4084015 58.0952072 58.7663574 58.7905502 59.593132 60.1586113 60.2161369 60.9365005 61.3168716 61.6175613 62.6060486 63.2958908 64.1942825 64.8860474 65.1414795 65.9292297 67.1208801 68.1343002 69.1395264 70.326149 71.2028503 71.4815445 72.1536102 72.2540131 73.3431244 73.7222443 74.7815094 76.7414093 78.2028198 78.6126556 79.1420898 80.5902557 81.9801788 83.5866852 84.7430573 86.0956268 87.8411102 89.2764893 90.4532623 91.6387939 92.0400085 93.3179474 93.7361145 94.8273697 96.7537308 99.3326874 102.494423 105.408203 108.280792 111.083862 116.169952 121.683762 126.939575 131.142914 140.304626 148.420044 178.083206 422.772705 ------------------------------ Transdef: Tab for variable 8 8.55078316 27.5328636 28.3106499 29.5276031 32.0615921 32.7662315 32.9905777 33.7739639 33.8985748 34.0588989 34.6923714 35.508522 36.1570435 36.3345413 36.5997162 37.0138397 37.7565613 38.362587 38.5774422 38.8201523 39.3394547 39.5426483 40.2539597 40.4244995 40.9660606 41.697876 41.7634239 42.3757629 42.6479568 43.1005554 43.1794815 43.6845512 43.6854401 44.1220665 44.1627808 44.2798424 44.477272 45.0492172 45.1793671 45.2406845 45.5003548 46.0288429 46.6800423 47.2313995 47.6132698 48.2296143 48.4494934 48.7188644 49.1921616 49.2058334 49.5755081 50.101757 50.7197266 51.0379105 51.1329727 51.6652374 52.1935005 52.7532959 53.016243 53.0191841 53.4014053 53.864563 54.3859177 54.8485031 55.2721062 55.7459488 56.2446022 57.0830345 57.4365616 57.9040298 58.2931442 58.819046 59.2986984 59.9150543 60.5180588 61.1001701 61.6914215 62.3456345 63.2389488 64.0638046 64.9213181 65.8273926 66.725296 67.3686218 68.4141235 69.5725174 70.2779999 71.524559 73.4775238 74.4520416 76.114624 78.110611 78.617012 79.2964249 81.7531281 85.2759094 88.1832275 91.7871323 98.749588 116.612137 351.972351 ------------------------------ Transdef: Tab for variable 9 56.5035744 61.4250908 67.1979675 68.8892517 69.8266602 71.9299393 71.9305496 73.9544678 74.4365921 75.2135315 75.2234039 77.0081024 77.0868988 78.706604 78.8943329 79.7682419 80.6520996 80.6521149 82.2651672 82.4259949 82.6911774 83.6759872 84.7210083 86.0511017 86.2072754 86.8973236 88.4309235 88.5266266 89.1145325 89.2325592 89.3371506 89.6485748 89.9925385 89.9953384 90.8473358 91.0899658 91.9674072 92.0312729 93.4243469 94.2770844 95.0380936 95.605484 95.6792297 96.6291885 97.596344 98.7615356 99.8364716 100.721558 101.37043 102.124611 102.929688 103.831535 104.830734 105.747574 106.271088 106.372345 107.241592 108.111679 108.704056 109.065277 109.202049 109.86496 110.337601 111.404251 112.092438 112.891212 113.778854 114.365082 115.166023 116.016571 116.882187 117.963013 118.785011 119.681503 120.690872 121.514191 122.420532 123.289459 124.01722 124.919464 126.05323 126.948425 127.628799 128.715622 129.824738 130.641556 131.386673 132.595154 134.482117 135.604004 136.951385 138.719208 139.935059 141.847153 143.720551 146.842804 148.147705 149.941589 155.571045 166.500153 389.79306 ------------------------------ Transdef: Tab for variable 10 0.154068351 1.06068897 1.41894412 1.59622872 1.75885844 1.84204721 1.8974551 1.9211061 2.00907278 2.06492376 2.15193462 2.22328281 2.24183631 2.27167892 2.31919122 2.3265152 2.37974548 2.43574905 2.46679091 2.47945428 2.49287534 2.52269411 2.55345035 2.58942175 2.61236 2.61389828 2.61761713 2.64291954 2.66887164 2.68723488 2.71070337 2.73260093 2.74620748 2.76671004 2.77353787 2.78058672 2.80755901 2.8247323 2.83643389 2.84119725 2.84538293 2.84841228 2.8632319 2.86361694 2.86713243 2.87218189 2.88746786 2.90459943 2.91682196 2.92710066 2.93626475 2.9505899 2.96005678 2.96765637 2.97516966 2.97853637 2.97916842 2.98398209 2.987391 2.99247169 3.00105667 3.00781202 3.01460481 3.01463413 3.02174568 3.0281949 3.02888417 3.03358531 3.03897071 3.04553628 3.05054092 3.05586958 3.0578413 3.0612607 3.06546688 3.06648636 3.07132387 3.07746768 3.08121395 3.0834465 3.08405924 3.08874965 3.09266019 3.09660625 3.09660649 3.10012007 3.10456705 3.10526729 3.10856724 3.10972977 3.1124537 3.11605883 3.11611533 3.11928773 3.12340426 3.12588644 3.13023305 3.13283753 3.13406754 3.13751984 3.14159226 ------------------------------ Transdef: Tab for variable 11 0.000443458557 0.00155878067 0.0168862343 0.0240619183 0.0317730308 0.0373311862 0.0407359302 0.0496929586 0.060593605 0.0722532272 0.08507967 0.0961937606 0.0974907875 0.106178761 0.116743863 0.130581677 0.137224674 0.141910553 0.142059803 0.154037833 0.155581892 0.164255381 0.170677722 0.179914355 0.188955188 0.20001781 0.208353281 0.209397912 0.219235778 0.231351614 0.242652059 0.254348278 0.264253676 0.267013073 0.268740416 0.273770452 0.278776169 0.281207085 0.287993312 0.298773766 0.306926936 0.315263569 0.315270901 0.32289803 0.330125332 0.3351475 0.344356835 0.345134318 0.351320684 0.351562619 0.358870268 0.367166042 0.374465466 0.378487587 0.385864139 0.390447855 0.395216525 0.398939252 0.403037816 0.40800494 0.413296759 0.418545723 0.424736142 0.433346391 0.435921669 0.437085092 0.444287539 0.451056927 0.45551616 0.459854424 0.465354204 0.470507026 0.473090112 0.480011106 0.490617692 0.492345631 0.496207595 0.507249713 0.509526193 0.517360568 0.521937191 0.523599863 0.527764082 0.530208528 0.534215808 0.536929727 0.545394838 0.545418859 0.55371213 0.557194829 0.566093326 0.578240633 0.595187008 0.61078763 0.626497626 0.640937507 0.668890357 0.702637792 0.727257013 0.802181244 1.1301049 ------------------------------ Transdef: Tab for variable 12 0.200248539 0.200248539 0.211730883 0.23933284 0.261999637 0.306726336 0.315550357 0.324374378 0.347894639 0.349879891 0.360201359 0.399811149 0.403345942 0.406367362 0.409647942 0.412763655 0.41601488 0.418145031 0.420416623 0.420790672 0.423255831 0.426583111 0.429345578 0.430036128 0.433611333 0.436812639 0.439434856 0.44298321 0.444978416 0.447925955 0.450400829 0.452893347 0.457180262 0.45725435 0.460990906 0.464025229 0.467373788 0.470015287 0.472885132 0.476621777 0.480011046 0.482852578 0.484712481 0.489312053 0.492533684 0.495197713 0.498191178 0.501432598 0.505746543 0.509782076 0.514113784 0.517946005 0.51813364 0.518548608 0.521843433 0.52366662 0.524703264 0.529462457 0.534754753 0.538423181 0.542302728 0.546499848 0.550112903 0.55670476 0.559631348 0.561818719 0.565819621 0.568210483 0.56877625 0.572834492 0.57728076 0.577424526 0.581221104 0.587241173 0.59224087 0.593857527 0.599425912 0.604771018 0.612318933 0.618746817 0.620240092 0.631823421 0.63859725 0.647353172 0.657274485 0.670213103 0.68256706 0.690366924 0.702626348 0.702665389 0.71337533 0.725110769 0.741089702 0.748691797 0.755490839 0.771235704 0.810346603 0.852643967 0.873316765 0.882444978 1.13453126 ------------------------------ Transdef: Tab for variable 13 20.0277634 21.5171661 22.374733 23.0090599 23.0102901 23.6645813 24.2440166 24.7597771 24.956398 25.1957951 25.8907967 26.424511 26.7396355 27.0175896 27.1215763 27.5466461 27.9384155 28.4265022 28.7731476 28.9828186 29.3332024 29.7216454 29.7968845 29.9610786 30.3568115 30.4528236 30.6954994 31.0663548 31.091877 31.4512444 31.7251415 31.9699039 32.0554199 32.3111801 32.3113289 32.3631935 32.6392822 32.6802177 32.8817368 33.0802574 33.3000336 33.6106873 33.6250229 33.8054276 33.9008675 34.1682968 34.5413971 34.725296 34.780899 35.167244 35.386116 35.4499054 35.8059158 36.0835495 36.1653976 36.3277359 36.4460144 36.8049393 37.0744858 37.3089752 37.7711296 38.1278343 38.1649094 38.5539665 38.5541992 38.8775177 39.1288109 39.5571899 40.00914 40.5591888 40.94524 41.33638 41.7208176 42.3973694 42.8526726 43.3669434 43.8493729 44.4725685 45.0751343 45.6816254 46.378582 47.0585403 47.0935898 47.6423607 48.5171204 49.5033226 50.4824333 51.4613495 52.8069077 54.5727539 54.9330978 55.2203217 55.4627304 56.8160248 58.878746 58.946228 60.3584442 63.4824333 67.5374832 75.3626251 121.136749 ------------------------------ Transdef: Tab for variable 14 10.028162 10.2623997 10.5828342 10.8578959 11.0574331 11.3119946 11.3946419 11.4188175 11.7640896 11.7961655 12.2712688 12.6787701 12.7131729 13.2008743 13.2675676 13.5891953 13.6256685 14.057354 14.5085707 14.5085974 14.8744459 15.3245468 15.6352081 15.971529 16.270874 16.3110771 16.3378925 16.5950279 16.5991058 16.9320297 16.9334297 17.3087196 17.5982285 18.0998459 18.4191628 18.9108543 19.0808849 19.2126656 19.5882778 19.8487358 20.0663986 20.3384399 20.5890465 20.7408867 20.8784142 21.1446419 21.1946831 21.3169098 21.3300476 21.5921631 21.9085007 21.9334106 22.0939255 22.2702808 22.6775246 22.9670067 23.3133812 23.6139145 23.7055397 23.9035511 24.1557465 24.5301208 24.8432007 25.1572552 25.4933205 25.7426434 25.9758797 26.264782 26.4492874 26.8958454 27.2441807 27.4856949 27.8898125 28.2357063 28.6685066 29.1216545 29.461071 29.9867325 30.2758102 30.743372 31.1260033 31.7473278 32.2056503 32.6841812 33.2045746 33.6614227 34.1772118 34.2193718 34.6309814 35.3104935 36.0747032 36.1069107 37.2710686 38.0994186 39.9531212 40.1766357 41.4163589 43.6186371 47.7214851 47.8448982 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 43.6 13.5 31.1 29.4 41.4 33.8 39.6 44.2 -12.4 4.3 18.0 8.1 24.1 2 43.6 100.0 45.5 37.8 30.3 66.2 92.6 68.6 84.1 -46.5 -17.0 -16.2 37.3 32.0 3 13.5 45.5 100.0 13.2 3.9 21.9 46.4 34.5 57.0 -3.8 -22.5 -22.1 84.9 11.0 4 31.1 37.8 13.2 100.0 12.9 26.1 35.6 39.1 48.2 -0.5 -26.8 -38.5 16.8 82.3 5 29.4 30.3 3.9 12.9 100.0 85.2 -5.2 53.7 64.4 30.8 0.4 15.3 -3.1 6.6 6 41.4 66.2 21.9 26.1 85.2 100.0 37.0 77.9 84.5 1.9 -6.3 5.0 13.4 18.6 7 33.8 92.6 46.4 35.6 -5.2 37.0 100.0 54.6 64.5 -58.3 -18.7 -24.0 40.3 32.3 8 39.6 68.6 34.5 39.1 53.7 77.9 54.6 100.0 80.2 -3.8 -15.1 -10.8 27.2 31.2 9 44.2 84.1 57.0 48.2 64.4 84.5 64.5 80.2 100.0 -8.9 -18.9 -13.9 46.0 38.8 10 -12.4 -46.5 -3.8 -0.5 30.8 1.9 -58.3 -3.8 -8.9 100.0 3.3 8.4 -5.3 -4.2 11 4.3 -17.0 -22.5 -26.8 0.4 -6.3 -18.7 -15.1 -18.9 3.3 100.0 53.4 -19.1 -26.4 12 18.0 -16.2 -22.1 -38.5 15.3 5.0 -24.0 -10.8 -13.9 8.4 53.4 100.0 -21.3 -28.7 13 8.1 37.3 84.9 16.8 -3.1 13.4 40.3 27.2 46.0 -5.3 -19.1 -21.3 100.0 30.9 14 24.1 32.0 11.0 82.3 6.6 18.6 32.3 31.2 38.8 -4.2 -26.4 -28.7 30.9 100.0 TOTAL CORRELATION TO TARGET (diagonal) 106.968838 TOTAL CORRELATION OF ALL VARIABLES 59.4046384 ROUND 1: MAX CORR ( 59.4045772) AFTER KILLING INPUT VARIABLE 14 CONTR 0.0852216649 ROUND 2: MAX CORR ( 59.3985104) AFTER KILLING INPUT VARIABLE 6 CONTR 0.848973934 ROUND 3: MAX CORR ( 59.3860625) AFTER KILLING INPUT VARIABLE 11 CONTR 1.21598707 ROUND 4: MAX CORR ( 59.277968) AFTER KILLING INPUT VARIABLE 10 CONTR 3.58147031 ROUND 5: MAX CORR ( 59.1507634) AFTER KILLING INPUT VARIABLE 7 CONTR 3.88132364 ROUND 6: MAX CORR ( 58.8690599) AFTER KILLING INPUT VARIABLE 13 CONTR 5.76598671 ROUND 7: MAX CORR ( 58.364195) AFTER KILLING INPUT VARIABLE 8 CONTR 7.69330559 ROUND 8: MAX CORR ( 57.8598629) AFTER KILLING INPUT VARIABLE 3 CONTR 7.65607744 ROUND 9: MAX CORR ( 57.757914) AFTER KILLING INPUT VARIABLE 9 CONTR 3.43323635 ROUND 10: MAX CORR ( 57.0273001) AFTER KILLING INPUT VARIABLE 5 CONTR 9.15771108 ROUND 11: MAX CORR ( 50.5040968) AFTER KILLING INPUT VARIABLE 4 CONTR 26.4848855 ROUND 12: MAX CORR ( 43.6209246) AFTER KILLING INPUT VARIABLE 12 CONTR 25.4534621 LAST REMAINING VARIABLE: 2 total correlation to target: 59.4046384 % total significance: 28.8109488 sigma correlations of single variables to target: variable 2: 43.6209246 % , in sigma: 21.1559275 variable 3: 13.5054209 % , in sigma: 6.55006073 variable 4: 31.0543913 % , in sigma: 15.0612225 variable 5: 29.3986715 % , in sigma: 14.2582068 variable 6: 41.3763085 % , in sigma: 20.0673001 variable 7: 33.7741158 % , in sigma: 16.3802751 variable 8: 39.6369769 % , in sigma: 19.2237331 variable 9: 44.2486476 % , in sigma: 21.46037 variable 10: -12.3862466 % , in sigma: 6.00726687 variable 11: 4.28772926 % , in sigma: 2.07952698 variable 12: 18.0493379 % , in sigma: 8.75383747 variable 13: 8.146955 % , in sigma: 3.95123191 variable 14: 24.1415832 % , in sigma: 11.7085456 variables sorted by significance: 1 most relevant variable 2 corr 43.6209259 , in sigma: 21.1559282 2 most relevant variable 12 corr 25.4534626 , in sigma: 12.3448005 3 most relevant variable 4 corr 26.4848862 , in sigma: 12.8450357 4 most relevant variable 5 corr 9.15771103 , in sigma: 4.44144347 5 most relevant variable 9 corr 3.43323636 , in sigma: 1.66510225 6 most relevant variable 3 corr 7.65607738 , in sigma: 3.71315876 7 most relevant variable 8 corr 7.69330549 , in sigma: 3.7312142 8 most relevant variable 13 corr 5.76598692 , in sigma: 2.79647445 9 most relevant variable 7 corr 3.88132358 , in sigma: 1.88242228 10 most relevant variable 10 corr 3.58147025 , in sigma: 1.73699493 11 most relevant variable 11 corr 1.21598709 , in sigma: 0.589747579 12 most relevant variable 6 corr 0.84897393 , in sigma: 0.411748056 13 most relevant variable 14 corr 0.0852216631 , in sigma: 0.041332075 global correlations between input variables: variable 2: 99.3041349 % variable 3: 95.1503283 % variable 4: 91.4637302 % variable 5: 97.7035375 % variable 6: 96.6512366 % variable 7: 99.1376646 % variable 8: 87.8135361 % variable 9: 99.0116568 % variable 10: 74.3571808 % variable 11: 57.5419173 % variable 12: 64.2352871 % variable 13: 90.6318082 % variable 14: 89.0956112 % significance loss when removing single variables: variable 2: corr = 10.403033 % , sigma = 5.04541833 variable 3: corr = 10.1691824 % , sigma = 4.93200198 variable 4: corr = 17.7633063 % , sigma = 8.6151136 variable 5: corr = 6.3103834 % , sigma = 3.06050399 variable 6: corr = 0.847619646 % , sigma = 0.411091236 variable 7: corr = 3.89546997 % , sigma = 1.88928321 variable 8: corr = 8.21189912 % , sigma = 3.98272949 variable 9: corr = 9.98031547 % , sigma = 4.84040246 variable 10: corr = 3.62775355 % , sigma = 1.7594421 variable 11: corr = 1.22053964 % , sigma = 0.591955545 variable 12: corr = 26.2960913 % , sigma = 12.7534711 variable 13: corr = 4.88924438 % , sigma = 2.37125876 variable 14: corr = 0.0852216649 % , sigma = 0.0413320759 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 2 --> 6.04051876 sigma out 15 active outputs RANK 2 NODE 5 --> 5.67441988 sigma out 15 active outputs RANK 3 NODE 3 --> 5.55268478 sigma out 15 active outputs RANK 4 NODE 4 --> 5.10531092 sigma out 15 active outputs RANK 5 NODE 1 --> 4.22139263 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 3 --> 5.80094194 sigma in 5act. ( 7.81799555 sig out 1act.) RANK 2 NODE 7 --> 4.52915382 sigma in 5act. ( 5.0812211 sig out 1act.) RANK 3 NODE 6 --> 4.40625477 sigma in 5act. ( 5.49711847 sig out 1act.) RANK 4 NODE 12 --> 4.28671598 sigma in 5act. ( 5.14690638 sig out 1act.) RANK 5 NODE 14 --> 3.27282858 sigma in 5act. ( 3.40605021 sig out 1act.) RANK 6 NODE 13 --> 3.16375542 sigma in 5act. ( 3.20643187 sig out 1act.) RANK 7 NODE 5 --> 3.07491255 sigma in 5act. ( 3.5702827 sig out 1act.) RANK 8 NODE 8 --> 2.75265408 sigma in 5act. ( 3.16383171 sig out 1act.) RANK 9 NODE 15 --> 2.26305318 sigma in 5act. ( 2.17053413 sig out 1act.) RANK 10 NODE 4 --> 2.00839233 sigma in 5act. ( 2.17166495 sig out 1act.) RANK 11 NODE 11 --> 1.21296668 sigma in 5act. ( 1.17272604 sig out 1act.) RANK 12 NODE 9 --> 1.16523218 sigma in 5act. ( 1.07246494 sig out 1act.) RANK 13 NODE 2 --> 0.954941809 sigma in 5act. ( 0.583226085 sig out 1act.) RANK 14 NODE 10 --> 0.673420548 sigma in 5act. ( 0.362844527 sig out 1act.) RANK 15 NODE 1 --> 0.588157237 sigma in 5act. ( 0.0175732039 sig out 1act.) sorted by output significance RANK 1 NODE 3 --> 7.81799555 sigma out 1act.( 5.80094194 sig in 5act.) RANK 2 NODE 6 --> 5.49711847 sigma out 1act.( 4.40625477 sig in 5act.) RANK 3 NODE 12 --> 5.14690638 sigma out 1act.( 4.28671598 sig in 5act.) RANK 4 NODE 7 --> 5.0812211 sigma out 1act.( 4.52915382 sig in 5act.) RANK 5 NODE 5 --> 3.5702827 sigma out 1act.( 3.07491255 sig in 5act.) RANK 6 NODE 14 --> 3.40605021 sigma out 1act.( 3.27282858 sig in 5act.) RANK 7 NODE 13 --> 3.20643187 sigma out 1act.( 3.16375542 sig in 5act.) RANK 8 NODE 8 --> 3.16383171 sigma out 1act.( 2.75265408 sig in 5act.) RANK 9 NODE 4 --> 2.17166495 sigma out 1act.( 2.00839233 sig in 5act.) RANK 10 NODE 15 --> 2.17053413 sigma out 1act.( 2.26305318 sig in 5act.) RANK 11 NODE 11 --> 1.17272604 sigma out 1act.( 1.21296668 sig in 5act.) RANK 12 NODE 9 --> 1.07246494 sigma out 1act.( 1.16523218 sig in 5act.) RANK 13 NODE 2 --> 0.583226085 sigma out 1act.( 0.954941809 sig in 5act.) RANK 14 NODE 10 --> 0.362844527 sigma out 1act.( 0.673420548 sig in 5act.) RANK 15 NODE 1 --> 0.0175732039 sigma out 1act.( 0.588157237 sig in 5act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 14.1673174 sigma in 15 active inputs SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 9.43768024 sigma out 15 active outputs RANK 2 NODE 5 --> 9.02747917 sigma out 15 active outputs RANK 3 NODE 3 --> 7.63506556 sigma out 15 active outputs RANK 4 NODE 4 --> 7.3187108 sigma out 15 active outputs RANK 5 NODE 2 --> 7.05058384 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 8 --> 7.61909294 sigma in 5act. ( 3.72985554 sig out 1act.) RANK 2 NODE 13 --> 7.18269062 sigma in 5act. ( 4.2573185 sig out 1act.) RANK 3 NODE 7 --> 5.97791767 sigma in 5act. ( 6.19873285 sig out 1act.) RANK 4 NODE 5 --> 5.44359064 sigma in 5act. ( 4.08153391 sig out 1act.) RANK 5 NODE 9 --> 5.25582695 sigma in 5act. ( 2.79847503 sig out 1act.) RANK 6 NODE 3 --> 5.25248003 sigma in 5act. ( 5.70532799 sig out 1act.) RANK 7 NODE 6 --> 5.22514677 sigma in 5act. ( 5.34475231 sig out 1act.) RANK 8 NODE 2 --> 4.57115173 sigma in 5act. ( 1.71335196 sig out 1act.) RANK 9 NODE 12 --> 4.19654799 sigma in 5act. ( 4.82212448 sig out 1act.) RANK 10 NODE 14 --> 3.50236249 sigma in 5act. ( 2.49977279 sig out 1act.) RANK 11 NODE 11 --> 3.4695456 sigma in 5act. ( 2.21348643 sig out 1act.) RANK 12 NODE 15 --> 2.22632027 sigma in 5act. ( 1.3101151 sig out 1act.) RANK 13 NODE 4 --> 2.17768502 sigma in 5act. ( 0.934634447 sig out 1act.) RANK 14 NODE 10 --> 1.04103076 sigma in 5act. ( 0.131552711 sig out 1act.) RANK 15 NODE 1 --> 1.00804555 sigma in 5act. ( 0.172958657 sig out 1act.) sorted by output significance RANK 1 NODE 7 --> 6.19873285 sigma out 1act.( 5.97791767 sig in 5act.) RANK 2 NODE 3 --> 5.70532799 sigma out 1act.( 5.25248003 sig in 5act.) RANK 3 NODE 6 --> 5.34475231 sigma out 1act.( 5.22514677 sig in 5act.) RANK 4 NODE 12 --> 4.82212448 sigma out 1act.( 4.19654799 sig in 5act.) RANK 5 NODE 13 --> 4.2573185 sigma out 1act.( 7.18269062 sig in 5act.) RANK 6 NODE 5 --> 4.08153391 sigma out 1act.( 5.44359064 sig in 5act.) RANK 7 NODE 8 --> 3.72985554 sigma out 1act.( 7.61909294 sig in 5act.) RANK 8 NODE 9 --> 2.79847503 sigma out 1act.( 5.25582695 sig in 5act.) RANK 9 NODE 14 --> 2.49977279 sigma out 1act.( 3.50236249 sig in 5act.) RANK 10 NODE 11 --> 2.21348643 sigma out 1act.( 3.4695456 sig in 5act.) RANK 11 NODE 2 --> 1.71335196 sigma out 1act.( 4.57115173 sig in 5act.) RANK 12 NODE 15 --> 1.3101151 sigma out 1act.( 2.22632027 sig in 5act.) RANK 13 NODE 4 --> 0.934634447 sigma out 1act.( 2.17768502 sig in 5act.) RANK 14 NODE 1 --> 0.172958657 sigma out 1act.( 1.00804555 sig in 5act.) RANK 15 NODE 10 --> 0.131552711 sigma out 1act.( 1.04103076 sig in 5act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 14.0015144 sigma in 15 active inputs *********************************************** *** Learn Path 1 *** loss function: -0.410470486 *** contribution from regularisation: 0.0235046726 *** contribution from error: -0.43397516 *********************************************** -----------------> Test sample --------------------------------------------------- Iteration : 2 *********************************************** *** Learn Path 2 *** loss function: -0.478845775 *** contribution from regularisation: 0.010967087 *** contribution from error: -0.489812851 *********************************************** -----------------> Test sample ENTER BFGS code START -2862.18 -0.820564806 -0.12075536 EXIT FROM BFGS code FG_START 0. -0.820564806 0. --------------------------------------------------- Iteration : 3 *********************************************** *** Learn Path 3 *** loss function: -0.492389053 *** contribution from regularisation: 0.00786817912 *** contribution from error: -0.500257254 *********************************************** -----------------> Test sample ENTER BFGS code FG_START -2942.51706 -0.820564806 0.0945941061 EXIT FROM BFGS code FG_LNSRCH 0. -0.820180118 0. --------------------------------------------------- Iteration : 4 *********************************************** *** Learn Path 4 *** loss function: -0.501857758 *** contribution from regularisation: 0.0133885881 *** contribution from error: -0.515246332 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -2999.1021 -0.820180118 15.2201834 EXIT FROM BFGS code NEW_X -2999.1021 -0.820180118 15.2201834 ENTER BFGS code NEW_X -2999.1021 -0.820180118 15.2201834 EXIT FROM BFGS code FG_LNSRCH 0. -0.79409498 0. --------------------------------------------------- Iteration : 5 *********************************************** *** Learn Path 5 *** loss function: -0.507820785 *** contribution from regularisation: 0.0115428343 *** contribution from error: -0.519363642 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3034.73687 -0.79409498 5.95717907 EXIT FROM BFGS code NEW_X -3034.73687 -0.79409498 5.95717907 ENTER BFGS code NEW_X -3034.73687 -0.79409498 5.95717907 EXIT FROM BFGS code FG_LNSRCH 0. -0.775353432 0. --------------------------------------------------- Iteration too many f3prim warnings -> stop : 6 *********************************************** *** Learn Path 6 *** loss function: -0.507604778 *** contribution from regularisation: 0.0118147032 *** contribution from error: -0.519419491 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3033.44604 -0.775353432 3.60970902 EXIT FROM BFGS code FG_LNSRCH 0. -0.790620148 0. --------------------------------------------------- Iteration : 7 *********************************************** *** Learn Path 7 *** loss function: -0.50767225 *** contribution from regularisation: 0.011753303 *** contribution from error: -0.519425571 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3033.84952 -0.790620148 5.64747143 EXIT FROM BFGS code FG_LNSRCH 0. -0.793762684 0. --------------------------------------------------- Iteration : 8 *********************************************** *** Learn Path 8 *** loss function: -0.507605553 *** contribution from regularisation: 0.01176304 *** contribution from error: -0.519368589 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3033.45096 -0.793762684 6.12090874 EXIT FROM BFGS code FG_LNSRCH 0. -0.794091403 0. --------------------------------------------------- Iteration : 9 *********************************************** *** Learn Path 9 *** loss function: -0.50668776 *** contribution from regularisation: 0.0126758842 *** contribution from error: -0.519363642 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3027.96602 -0.794091403 5.97558689 EXIT FROM BFGS code FG_LNSRCH 0. -0.79409498 0. --------------------------------------------------- Iteration : 10 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 7.45309448 sigma out 15 active outputs RANK 2 NODE 5 --> 7.00792027 sigma out 15 active outputs RANK 3 NODE 3 --> 6.74118662 sigma out 15 active outputs RANK 4 NODE 4 --> 5.23066092 sigma out 15 active outputs RANK 5 NODE 2 --> 4.62446928 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 8 --> 6.72240973 sigma in 5act. ( 4.5015645 sig out 1act.) RANK 2 NODE 13 --> 6.3224287 sigma in 5act. ( 4.37742376 sig out 1act.) RANK 3 NODE 9 --> 4.78722095 sigma in 5act. ( 3.4755106 sig out 1act.) RANK 4 NODE 7 --> 4.64419079 sigma in 5act. ( 3.71401286 sig out 1act.) RANK 5 NODE 6 --> 4.02001667 sigma in 5act. ( 3.71352768 sig out 1act.) RANK 6 NODE 5 --> 3.91950727 sigma in 5act. ( 3.13811374 sig out 1act.) RANK 7 NODE 2 --> 3.69689775 sigma in 5act. ( 2.71787167 sig out 1act.) RANK 8 NODE 11 --> 2.8055284 sigma in 5act. ( 2.18631029 sig out 1act.) RANK 9 NODE 14 --> 2.17247915 sigma in 5act. ( 1.4381212 sig out 1act.) RANK 10 NODE 12 --> 1.97071922 sigma in 5act. ( 1.44386709 sig out 1act.) RANK 11 NODE 3 --> 1.77558362 sigma in 5act. ( 0.7096048 sig out 1act.) RANK 12 NODE 15 --> 1.32985413 sigma in 5act. ( 0.44812879 sig out 1act.) RANK 13 NODE 4 --> 1.31768167 sigma in 5act. ( 0.141292542 sig out 1act.) RANK 14 NODE 1 --> 0.678201675 sigma in 5act. ( 0.330935389 sig out 1act.) RANK 15 NODE 10 --> 0.645621181 sigma in 5act. ( 0.00142904755 sig out 1 act.) sorted by output significance RANK 1 NODE 8 --> 4.5015645 sigma out 1act.( 6.72240973 sig in 5act.) RANK 2 NODE 13 --> 4.37742376 sigma out 1act.( 6.3224287 sig in 5act.) RANK 3 NODE 7 --> 3.71401286 sigma out 1act.( 4.64419079 sig in 5act.) RANK 4 NODE 6 --> 3.71352768 sigma out 1act.( 4.02001667 sig in 5act.) RANK 5 NODE 9 --> 3.4755106 sigma out 1act.( 4.78722095 sig in 5act.) RANK 6 NODE 5 --> 3.13811374 sigma out 1act.( 3.91950727 sig in 5act.) RANK 7 NODE 2 --> 2.71787167 sigma out 1act.( 3.69689775 sig in 5act.) RANK 8 NODE 11 --> 2.18631029 sigma out 1act.( 2.8055284 sig in 5act.) RANK 9 NODE 12 --> 1.44386709 sigma out 1act.( 1.97071922 sig in 5act.) RANK 10 NODE 14 --> 1.4381212 sigma out 1act.( 2.17247915 sig in 5act.) RANK 11 NODE 3 --> 0.7096048 sigma out 1act.( 1.77558362 sig in 5act.) RANK 12 NODE 15 --> 0.44812879 sigma out 1act.( 1.32985413 sig in 5act.) RANK 13 NODE 1 --> 0.330935389 sigma out 1act.( 0.678201675 sig in 5act.) RANK 14 NODE 4 --> 0.141292542 sigma out 1act.( 1.31768167 sig in 5act.) RANK 15 NODE 10 --> 0.00142904755 sigma out 1act.( 0.645621181 sig in 5act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 10.3000298 sigma in 15 active inputs *********************************************** *** Learn Path 10 *** loss function: -0.507622302 *** contribution from regularisation: 0.0117412899 *** contribution from error: -0.519363582 *********************************************** -----------------> Test sample Iteration No: 10 ********************************************** ***** write out current network **** ***** to "rescue.nb" **** ********************************************** SAVING EXPERTISE TO rescue.nb ENTER BFGS code FG_LNSRCH -3033.5509 -0.79409498 5.34949112 EXIT FROM BFGS code FG_LNSRCH 0. -0.79409498 0. --------------------------------------------------- Iteration : 11 *********************************************** *** Learn Path 11 *** loss function: -0.509173691 *** contribution from regularisation: 0.0101898974 *** contribution from error: -0.519363582 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3042.82202 -0.79409498 6.5744257 EXIT FROM BFGS code FG_LNSRCH 0. -0.79409498 0. --------------------------------------------------- Iteration : 12 *********************************************** *** Learn Path 12 *** loss function: -0.506104112 *** contribution from regularisation: 0.0132594649 *** contribution from error: -0.519363582 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3024.47829 -0.79409498 5.75070906 EXIT FROM BFGS code FG_LNSRCH 0. -0.79409498 0. --------------------------------------------------- Iteration : 13 *********************************************** *** Learn Path 13 *** loss function: -0.50818789 *** contribution from regularisation: 0.0111757098 *** contribution from error: -0.519363582 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -3036.93081 -0.79409498 5.74843407 EXIT FROM BFGS code NEW_X -3036.93081 -0.79409498 5.74843407 ENTER BFGS code NEW_X -3036.93081 -0.79409498 5.74843407 EXIT FROM BFGS code FG_LNSRCH 0. 4.95433903 0. --------------------------------------------------- Iteration : 14