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= 17278 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 = 4447 nbkg = 12831 Bkg Entries: 12831 Sig Entries: 4447 Chosen entries: 4447 Warning: entries low (below 6000) Signal fraction: 1 Background fraction: 0.346583 Signal Tree Copy Condition: Background Tree Copy Condition: Actual Background Entries: 12831 Actual Signal Entries: 4447 Entries to split: 4447 Test with : 2223 Train with : 2223 ********************************************* * 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= 4447 for Signal Prepared event 0 for Signal with 4447 events ====Entry 0 Variable Ht : 137.556 Variable LepAPt : 28.7683 Variable LepBPt : 22.0275 Variable MetSigLeptonsJets : 2.53452 Variable MetSpec : 25.5479 Variable SumEtLeptonsJets : 110.868 Variable VSumJetLeptonsPt : 10.7432 Variable addEt : 77.4833 Variable dPhiLepSumMet : 1.92733 Variable dPhiLeptons : 0.404886 Variable dRLeptons : 0.564536 Variable lep1_E : 29.8734 Variable lep2_E : 22.1792 ===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 = 137.556 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 28.7683 LepAPt = 28.7683 LepBEt = 22.0279 LepBPt = 22.0275 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 26.687 MetDelPhi = 1.27756 MetSig = 1.80898 MetSigLeptonsJets = 2.53452 MetSpec = 25.5479 Mjj = 0 MostCentralJetEta = 1.45306 MtllMet = 78.5497 Njets = 1 SB = 0 SumEt = 217.637 SumEtJets = 0 SumEtLeptonsJets = 110.868 Target = 1 TrainWeight = 1 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 10.7432 addEt = 77.4833 dPhiLepSumMet = 1.92733 dPhiLeptons = 0.404886 dRLeptons = 0.564536 diltype = 54 dimass = 14.2079 event = 4318 jet1_Et = 60.0726 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 29.8734 lep2_E = 22.1792 rand = 0.999742 run = 237478 weight = 2.9793e-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= 12831 for Background Prepared event 0 for Background with 12831 events ====Entry 0 Variable Ht : 61.1273 Variable LepAPt : 22.7899 Variable LepBPt : 11.7315 Variable MetSigLeptonsJets : 4.52817 Variable MetSpec : 26.6052 Variable SumEtLeptonsJets : 34.5213 Variable VSumJetLeptonsPt : 31.9684 Variable addEt : 61.1273 Variable dPhiLepSumMet : 2.92616 Variable dPhiLeptons : 0.819534 Variable dRLeptons : 0.934366 Variable lep1_E : 23.1166 Variable lep2_E : 12.194 ===Show Start ======> EVENT:0 DEtaJ1J2 = 0 DEtaJ1Lep1 = 0 DEtaJ1Lep2 = 0 DEtaJ2Lep1 = 0 DEtaJ2Lep2 = 0 DPhiJ1J2 = 0 DPhiJ1Lep1 = 0 DPhiJ1Lep2 = 0 DPhiJ2Lep1 = 0 DPhiJ2Lep2 = 0 DRJ1J2 = 0 DRJ1Lep1 = 0 DRJ1Lep2 = 0 DRJ2Lep1 = 0 DRJ2Lep2 = 0 DeltaRJet12 = 0 File = 1 Ht = 61.1273 IsMEBase = 0 LRHWW = 0 LRWW = 0 LRWg = 0 LRWj = 0 LRZZ = 0 LepAEt = 22.7899 LepAPt = 22.7899 LepBEt = 11.7322 LepBPt = 11.7315 LessCentralJetEta = 0 MJ1Lep1 = 0 MJ1Lep2 = 0 MJ2Lep1 = 0 MJ2Lep2 = 0 NN = 0 Met = 26.6052 MetDelPhi = 2.37814 MetSig = 2.46258 MetSigLeptonsJets = 4.52817 MetSpec = 26.6052 Mjj = 0 MostCentralJetEta = 0 MtllMet = 61.9133 Njets = 0 SB = 0 SumEt = 116.722 SumEtJets = 0 SumEtLeptonsJets = 34.5213 Target = 0 TrainWeight = 2.45577 VSum2JetLeptonsPt = 0 VSum2JetPt = 0 VSumJetLeptonsPt = 31.9684 addEt = 61.1273 dPhiLepSumMet = 2.92616 dPhiLeptons = 0.819534 dRLeptons = 0.934366 diltype = 54 dimass = 14.9851 event = 1421455 jet1_Et = 0 jet1_eta = 0 jet2_Et = 0 jet2_eta = 0 lep1_E = 23.1166 lep2_E = 12.194 rand = 0.999742 run = 271216 weight = 0.0400324 ===Show End Prepared event 10000 for Background with 12831 events Warning: found 386 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 17278 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 386 negative weights. Signal fraction: 74.9768829 % ------------------------------ 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 55.8076553 66.3799438 68.4831848 70.7022324 71.0074005 73.4048462 75.0432129 75.6999817 77.1744537 78.8890991 80.8918991 80.972702 81.552948 82.3304901 83.3777847 83.5448456 84.65448 85.3290558 86.5702972 86.878212 88.5322952 88.6497345 90.0822372 91.2347565 92.9191132 94.0936127 95.4396286 96.6770401 97.2944946 98.4013901 98.8800201 99.7229462 100.828888 101.522354 102.239853 103.686234 104.804649 105.495697 106.338486 106.985992 107.946182 108.618866 110.011902 111.676529 112.875305 114.363876 115.488937 116.872574 117.793793 119.284378 120.420929 121.368248 122.822418 123.745041 125.261185 126.130707 127.053314 127.861404 128.738525 129.799072 131.055634 132.199524 133.195007 133.712311 134.93367 136.586121 137.78714 138.966553 140.308044 141.57428 142.537247 143.954712 145.569916 146.925659 148.115295 149.651733 151.210587 153.320648 155.342377 158.002213 159.783478 161.811737 163.5849 166.000854 168.888504 171.847107 174.631561 177.308929 181.046127 184.817993 188.444336 192.045746 196.41832 202.470764 209.889282 216.190765 223.558395 238.720459 262.817322 298.687744 519.386597 ------------------------------ Transdef: Tab for variable 3 20.0008526 20.5759888 21.0332355 21.3882771 21.6675186 22.02001 22.2019196 22.5349159 22.6711845 23.0634575 23.217411 23.6158829 23.8068085 23.9170971 24.3179893 24.6678257 25.0016556 25.1728325 25.2569771 25.4215317 25.6513367 25.8939171 26.0858307 26.1960258 26.5144291 26.8335533 27.0881805 27.2230568 27.3543701 27.6005383 27.8206024 27.9785614 28.1446037 28.3192635 28.4134197 28.6184788 28.6679802 28.7340126 28.9096851 29.1049023 29.3371124 29.5659714 29.6661301 29.7306957 29.9757462 30.1268349 30.2584953 30.5040054 30.7424622 30.9532318 31.239151 31.4697418 31.6750412 31.84729 32.088089 32.324028 32.6061783 32.7593155 32.9594498 33.1134109 33.3194885 33.5983734 33.7413101 33.8813248 34.1442642 34.2852669 34.5703125 34.7775497 34.992157 35.176136 35.4264069 35.5966759 35.6952629 35.9408989 36.1137848 36.4526672 36.6212578 36.7315369 37.004467 37.3789406 37.7371559 38.2608948 38.6873474 39.0552177 39.5261383 39.958271 40.4199753 40.8234024 41.4220276 41.9480057 42.6430054 43.323246 43.8112411 44.8851852 45.745285 47.249157 47.9133835 49.4850006 52.1898041 57.9194984 109.76886 ------------------------------ Transdef: Tab for variable 4 10.0013514 10.1119308 10.200943 10.3642769 10.4312077 10.492897 10.548213 10.6639662 10.7953577 10.9232054 10.9564123 11.1205654 11.2442379 11.3224812 11.5010986 11.6088114 11.7589684 11.8555565 12.0300608 12.1905699 12.3060036 12.5259342 12.7743254 12.8468094 13.0912685 13.2897396 13.4710674 13.6081247 13.6176329 13.7753115 13.8242836 14.0369959 14.3346291 14.7238712 15.0182629 15.2600231 15.5959988 15.8159256 15.9525251 16.0114212 16.3192062 16.3983192 16.6684189 16.8391991 17.0685081 17.3678646 17.646698 17.9232483 18.2312088 18.4469376 18.754158 19.0656281 19.2074871 19.4568024 19.7393761 20.031517 20.2342396 20.3935471 20.6258926 20.7786884 20.9689293 21.1589088 21.3113937 21.4888954 21.7465591 21.8786411 22.0607758 22.200901 22.4360676 22.6392174 22.8296509 23.0329628 23.2939167 23.5263786 23.803894 24.016922 24.3564796 24.5075626 24.6902714 24.9560356 25.1631317 25.3782043 25.615284 25.8940372 26.060379 26.3129425 26.5689392 27.014431 27.3137989 27.7126389 28.0587559 28.3097591 28.6705093 29.0686722 29.4995155 29.9277954 30.5576134 31.4555664 32.3306198 33.8775673 38.3761635 ------------------------------ Transdef: Tab for variable 5 2.1499095 3.27847004 3.63101578 3.93333316 4.12005091 4.22924709 4.44208813 4.61276245 4.78674936 4.86451101 4.95603657 5.01634121 5.13221073 5.17595005 5.26455212 5.33557177 5.38349628 5.44987059 5.50640154 5.52401161 5.54310322 5.64003754 5.70739508 5.75129318 5.84093428 5.93808508 6.0334053 6.11316109 6.18638992 6.29348183 6.33180237 6.4126091 6.47459126 6.53812313 6.59848309 6.63857841 6.65952015 6.7006216 6.73455811 6.77702522 6.81726646 6.83365726 6.87176371 6.89411926 6.92140388 6.94232464 7.01393032 7.0557909 7.1044178 7.16011143 7.18371487 7.21274757 7.27790165 7.32473564 7.37565422 7.39297199 7.43219376 7.49263668 7.53292561 7.56011868 7.58991289 7.63920975 7.66925478 7.71397495 7.76192331 7.81854534 7.86383724 7.91100883 7.94509602 7.98001766 8.03483582 8.09671211 8.14299583 8.21062088 8.2494812 8.27966499 8.33317852 8.39439583 8.42472553 8.47444344 8.5303421 8.59655571 8.65511513 8.72141171 8.77965546 8.85228539 8.91991425 8.98510551 9.06553936 9.1445713 9.22322273 9.33152008 9.48712826 9.63370705 9.81905746 9.94743347 10.1747856 10.4954281 11.0478601 11.9349594 16.3801937 ------------------------------ Transdef: Tab for variable 6 25.0010986 27.1630058 29.0595932 29.9752693 30.7931442 31.2472534 31.953661 32.6545563 33.3232727 34.0589485 34.5044174 34.7506027 35.6869202 36.1756783 37.3426285 38.2224274 38.7409019 39.6458817 39.99366 40.6954346 41.4995041 42.1996002 42.422657 42.4973946 42.7949524 42.9860573 43.1447144 43.7624893 43.8904839 44.4500656 45.1138611 45.7887039 46.4453621 46.9990234 47.4042587 47.9194946 48.1121292 48.4280548 49.1141052 49.4017105 49.7618752 50.0436935 50.3331299 50.4980927 50.7516556 51.4325638 51.9297485 52.5934372 53.2318954 53.8622398 54.400383 55.0273972 55.362339 55.6677933 56.2286682 56.5628853 57.0300369 57.5863953 58.0815506 58.3857956 58.8721085 59.3960762 60.1280365 60.903389 61.505722 62.2607727 62.8202133 63.509491 64.0801392 64.8709793 65.5546875 66.2097015 66.7643356 67.5140762 68.2325287 68.6860733 69.4693832 70.1322937 70.9858246 71.4935455 72.272789 72.9125519 73.6323242 74.4300385 75.2162781 76.1652374 77.7049713 78.7933655 80.0561447 81.2700119 82.9180756 84.8459778 86.8937073 89.1747589 91.5937958 94.2867355 97.6832581 103.432114 111.522507 123.292709 214.990372 ------------------------------ Transdef: Tab for variable 7 30.250906 33.6397858 34.8966675 35.3932228 36.2691422 36.8764534 37.5292053 38.3838272 38.5646706 38.7752686 38.8870621 39.3411064 39.7575264 39.9870567 40.5193863 40.8964348 41.4486618 41.7108994 42.503006 42.7331543 43.3375626 44.3077431 44.9043427 45.3660202 45.7868652 46.2306137 46.7120132 47.026371 47.6665649 48.2461853 48.7094803 49.3942299 49.7375488 50.4356384 50.9944382 51.3213577 52.1003151 52.5540733 53.4618835 54.249897 54.9951439 55.9313736 56.5413551 57.0306435 57.7722626 58.2535782 58.9135818 59.9042816 60.4706192 61.1992188 61.8881607 62.4703827 62.8283691 63.5020752 64.344635 64.8547211 65.6940765 66.3001099 66.9788055 67.8616333 68.6435242 69.0413513 70.1053772 70.7321472 71.5217743 72.431839 73.0657043 74.4131165 75.2437744 76.4159241 77.4817429 78.8764648 79.8191452 81.3788834 82.3245163 83.4258575 84.5923157 86.0085754 87.637352 89.073555 90.9456024 93.0891266 95.1127701 96.930069 99.3088226 101.674088 103.774643 106.336037 107.971443 110.090485 112.422928 114.696121 118.12886 123.563797 128.514374 132.790833 139.022583 145.133453 158.596008 180.946686 338.360565 ------------------------------ Transdef: Tab for variable 8 6.80322456 25.3597946 30.093504 32.5732269 33.4344254 33.8007965 34.1098862 34.611496 35.4300156 35.5259438 36.1161232 37.0209961 37.384491 37.6673126 37.9404259 38.2076874 38.7844009 38.8855553 39.2657242 39.5577087 39.7195358 39.8317871 40.2770538 40.9216309 41.3534355 41.6937141 42.1768036 42.6809196 42.9854355 43.3714561 43.6970673 44.1075287 44.4106178 44.8382339 45.2169456 45.7537842 46.0195351 46.5830002 46.7991829 47.4088364 47.8839607 48.225769 48.6664963 48.7481117 48.8063774 49.0505447 49.3811646 49.9347076 50.1622772 50.6609917 51.3021851 52.0721245 52.5325241 53.0130653 53.4834747 54.0422859 54.4676628 55.150486 55.7644043 56.4525185 56.9223404 57.4922562 58.1239662 58.2993736 58.7801323 59.3292694 59.9067078 60.5011444 61.0428467 61.5827866 62.041153 62.4971161 62.9871292 63.6084061 64.0668945 64.8061981 65.3461456 65.92202 66.6799011 67.3867569 67.925293 68.7594147 69.3444214 70.1147919 71.3589096 72.405777 73.4648743 74.5452271 75.4769745 77.0381012 78.4777298 80.0367737 81.382225 85.0176239 88.4676208 93.2902832 97.9678955 102.993408 111.266312 127.904861 219.619247 ------------------------------ Transdef: Tab for variable 9 55.8076553 64.9339752 68.2638855 69.6990051 70.7022324 70.9990082 73.0340347 74.6603088 75.5134888 77.059166 78.3524017 79.3022919 80.5946503 80.972702 81.3537445 82.1420135 82.8007507 83.3714828 83.6518707 84.65448 85.3267975 86.0229187 86.6680374 88.1560516 88.6373825 89.309845 90.0957489 90.5669327 91.2775726 92.1981506 93.2106552 93.9414368 94.9712677 95.4403534 96.720726 97.1182175 97.9528351 98.4013901 98.904747 99.7536469 100.492226 101.137245 101.633537 102.290237 103.325455 104.260719 104.806984 105.392944 106.336884 106.838799 107.946182 108.471008 109.141525 109.972725 111.035355 111.897827 112.771484 113.911079 114.73159 114.999146 115.560318 116.343529 117.205933 117.890915 119.091606 119.972412 120.718399 121.515945 122.31517 123.059464 123.764862 124.699203 125.685455 126.522415 127.421844 128.278473 128.995407 130.153748 131.019348 132.043152 132.897339 134.004517 135.112793 136.392578 137.409973 138.484467 139.392899 140.52594 141.972412 143.316925 144.553131 145.776611 147.549545 149.689819 151.434357 153.701416 156.46991 161.08078 167.78653 182.63504 282.530121 ------------------------------ Transdef: Tab for variable 10 0.364058048 0.941168666 1.29481173 1.50234866 1.68127394 1.82899415 1.91628373 1.9847188 2.08408427 2.13911009 2.19440842 2.25124216 2.31882191 2.36036968 2.39591122 2.4282136 2.46249294 2.4900744 2.5110805 2.54064465 2.56572151 2.58187771 2.61169624 2.63280702 2.65368509 2.6784296 2.6951468 2.71599102 2.73318172 2.75021935 2.765728 2.78513026 2.80054736 2.81804347 2.83223009 2.84484243 2.85347223 2.85721707 2.86537123 2.87635994 2.88377666 2.89503479 2.904145 2.91320229 2.91741467 2.92683363 2.93770838 2.94673157 2.9522562 2.95844603 2.96247768 2.96617746 2.9758954 2.98214579 2.98982048 2.99308634 2.99961042 3.00394702 3.0091188 3.01235843 3.01732111 3.02335143 3.02837801 3.03355312 3.03718591 3.03989363 3.04636717 3.0518322 3.05369949 3.05691051 3.05923223 3.06381941 3.065938 3.0671804 3.07185841 3.07419634 3.07643414 3.07870626 3.08096552 3.08292246 3.08856511 3.0918355 3.09415531 3.09562111 3.10098982 3.10327148 3.10444736 3.10585022 3.10997963 3.11303425 3.11498737 3.1180768 3.12090874 3.12256813 3.12796926 3.12932134 3.13169551 3.13251662 3.13489819 3.13865232 3.14157605 ------------------------------ Transdef: Tab for variable 11 0.00017022471 0.0112676546 0.0173919797 0.0237872526 0.0363558605 0.0470670909 0.055095911 0.0607652366 0.0706255138 0.0817972049 0.0908839703 0.0947299004 0.104617417 0.113437027 0.123355985 0.132520199 0.141396344 0.153537989 0.160110176 0.167569906 0.17853725 0.18887879 0.199229717 0.208438516 0.219007254 0.230307147 0.234397754 0.23998332 0.252686143 0.25871408 0.263660491 0.272205472 0.279336572 0.289218485 0.298149884 0.30621779 0.313534856 0.319095433 0.323471904 0.328633934 0.333255172 0.341757417 0.345934212 0.352757335 0.358349562 0.36147368 0.368898422 0.372934997 0.377605766 0.380883515 0.386420667 0.388403416 0.391155183 0.393162966 0.397968709 0.400298238 0.403853923 0.407461762 0.410449177 0.4148314 0.417830259 0.422498107 0.427260816 0.432437599 0.436087191 0.439079046 0.43942672 0.443549663 0.446440399 0.447905004 0.452416688 0.456389666 0.459079742 0.466042995 0.47361505 0.480521441 0.490334868 0.497885346 0.505268037 0.512760162 0.517737031 0.523983479 0.528215766 0.534265637 0.542262077 0.557408452 0.570080757 0.576927066 0.586774945 0.600944042 0.610477805 0.623133063 0.631899357 0.644906282 0.650444686 0.663661718 0.694087267 0.726957619 0.76424396 0.798737288 1.0973314 ------------------------------ Transdef: Tab for variable 12 0.2193266 0.401326776 0.404307187 0.407688141 0.410552025 0.41250065 0.41361779 0.416085541 0.418745279 0.421096951 0.424059331 0.426768601 0.428173989 0.430217326 0.432894498 0.435757399 0.437521428 0.439503998 0.441803336 0.44424358 0.445930868 0.448818594 0.452157199 0.454710662 0.457755983 0.459820688 0.462776035 0.464776427 0.467212021 0.469462395 0.471265376 0.472355545 0.47453782 0.477137566 0.479669094 0.482188344 0.484451592 0.487152517 0.489764035 0.491095126 0.494153023 0.497282982 0.500471711 0.504580319 0.507739782 0.510629058 0.513140082 0.515791535 0.518638492 0.521584868 0.524499893 0.528479338 0.532363176 0.535169005 0.537675142 0.542667031 0.548738718 0.553457856 0.556964517 0.55920279 0.562586784 0.565969348 0.567811728 0.57039386 0.574462175 0.579199791 0.584758937 0.590406001 0.595893025 0.601723194 0.608252764 0.613603711 0.619459987 0.625084281 0.629567981 0.636998177 0.646133304 0.651482284 0.655901074 0.662196577 0.66607362 0.67183727 0.675291538 0.678180337 0.681097627 0.694125831 0.700617969 0.713075459 0.715544641 0.721473098 0.733284593 0.746145606 0.753971696 0.768598437 0.781390786 0.796113133 0.805377245 0.842329025 0.87710464 0.915660977 1.12224686 ------------------------------ Transdef: Tab for variable 13 20.1928711 22.1593094 22.8542862 23.5495148 24.2342873 24.9068794 25.2412224 25.7471924 26.1549549 26.729908 27.0821152 27.5039997 27.9073601 28.1749229 28.761219 29.1686554 29.579483 29.9437809 30.3349876 30.5381775 30.6539326 30.9059124 31.083725 31.5734138 32.0765991 32.4562683 32.8982887 33.1077042 33.3389206 33.7832184 34.2562637 34.417675 34.9354477 35.3028717 35.4444427 35.6463776 35.9690094 36.0530624 36.1880341 36.505188 36.8008575 37.1324272 37.456337 38.0135727 38.5508499 38.7442589 39.2546616 39.7995834 40.0435791 40.3792191 40.6327286 40.9722824 41.2960663 41.7425156 42.1208801 42.5449448 43.046196 43.4162521 43.5838623 44.0543289 44.3977966 44.7228737 45.2388611 45.789772 46.2511444 46.4356575 47.0048294 47.4598007 47.8731384 48.362709 48.7296219 49.5800705 50.4061165 50.8171082 51.1973038 52.2177887 52.8488426 53.7797813 54.5754852 55.2277145 56.1401291 57.1085052 58.6787872 59.7673645 60.3468361 61.7687607 63.0456772 64.1443787 64.5089874 66.7160416 67.3453293 68.4884949 71.8119431 74.0547333 77.3695221 81.0138245 82.9963379 85.3630829 89.9152374 98.3802948 191.718018 ------------------------------ Transdef: Tab for variable 14 10.0093269 10.5734663 10.8874636 11.0025539 11.4353371 11.8563938 12.3120346 12.469944 12.8379316 13.1080856 13.6377697 13.8346148 13.9734478 14.4496498 14.8808842 15.1171684 15.8951855 16.1783218 16.3769798 16.4593353 16.756073 16.9194069 17.2984505 17.7027168 17.8201599 18.1616516 18.1829147 18.4038887 18.6948204 18.8955936 19.0870857 19.2337074 19.4866676 19.8739777 20.147234 20.4801846 20.8119469 21.1538429 21.5092239 21.666172 21.7486534 21.9470673 22.0738564 22.3486271 22.4755039 22.7865181 23.0312099 23.2035103 23.4374905 23.6669807 24.035614 24.394619 24.5519714 24.7697105 25.0135155 25.249012 25.5745697 25.8464928 26.0945072 26.4399109 26.6117401 27.0270767 27.3025551 27.5553665 27.8288956 28.116745 28.1761436 28.5274353 28.7793808 29.0986176 29.3560181 29.7765293 30.2188797 30.7085266 31.0828171 31.4529228 31.9389362 32.3751793 32.8462524 33.3188705 33.8262863 34.3942642 34.9265251 35.6819839 36.2891922 36.8410263 37.6368866 38.5468063 39.4569092 40.534523 41.5110168 42.6888618 44.1570358 45.9940262 47.5128708 49.0471802 50.9170303 53.1837578 57.0900688 63.0269051 89.625824 COVARIANCE MATRIX (IN PERCENT) 0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 0 0.9 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1 100.0 53.3 17.8 47.5 17.6 37.3 52.7 42.4 48.3 -29.6 -10.6 -23.7 -0.3 38.1 2 53.3 100.0 41.8 45.5 37.8 73.5 93.8 75.2 88.2 -48.1 -16.2 -33.3 14.9 34.0 3 17.8 41.8 100.0 21.1 5.2 25.0 44.6 36.6 52.9 -3.9 -22.8 -43.1 56.1 11.8 4 47.5 45.5 21.1 100.0 17.7 35.8 44.8 44.8 55.4 -4.6 -21.2 -54.7 5.8 78.8 5 17.6 37.8 5.2 17.7 100.0 83.2 6.8 51.6 66.1 21.1 -5.6 -12.4 -5.6 12.3 6 37.3 73.5 25.0 35.8 83.2 100.0 50.7 77.5 87.3 -8.5 -10.9 -25.1 4.6 26.8 7 52.7 93.8 44.6 44.8 6.8 50.7 100.0 66.8 73.0 -57.7 -16.5 -32.5 18.5 33.7 8 42.4 75.2 36.6 44.8 51.6 77.5 66.8 100.0 81.9 -15.5 -17.5 -33.0 15.2 34.6 9 48.3 88.2 52.9 55.4 66.1 87.3 73.0 81.9 100.0 -18.9 -20.5 -44.0 20.3 40.9 10 -29.6 -48.1 -3.9 -4.6 21.1 -8.5 -57.7 -15.5 -18.9 100.0 1.2 -2.5 2.3 -4.9 11 -10.6 -16.2 -22.8 -21.2 -5.6 -10.9 -16.5 -17.5 -20.5 1.2 100.0 50.7 -21.7 -23.5 12 -23.7 -33.3 -43.1 -54.7 -12.4 -25.1 -32.5 -33.0 -44.0 -2.5 50.7 100.0 -24.7 -44.6 13 -0.3 14.9 56.1 5.8 -5.6 4.6 18.5 15.2 20.3 2.3 -21.7 -24.7 100.0 31.8 14 38.1 34.0 11.8 78.8 12.3 26.8 33.7 34.6 40.9 -4.9 -23.5 -44.6 31.8 100.0 TOTAL CORRELATION TO TARGET (diagonal) 130.488856 TOTAL CORRELATION OF ALL VARIABLES 62.1464047 ROUND 1: MAX CORR ( 62.1433912) AFTER KILLING INPUT VARIABLE 11 CONTR 0.612004355 ROUND 2: MAX CORR ( 62.1346485) AFTER KILLING INPUT VARIABLE 2 CONTR 1.04236264 ROUND 3: MAX CORR ( 62.1097274) AFTER KILLING INPUT VARIABLE 8 CONTR 1.75963128 ROUND 4: MAX CORR ( 62.0807499) AFTER KILLING INPUT VARIABLE 6 CONTR 1.89703445 ROUND 5: MAX CORR ( 61.9626632) AFTER KILLING INPUT VARIABLE 12 CONTR 3.82725358 ROUND 6: MAX CORR ( 61.6174692) AFTER KILLING INPUT VARIABLE 14 CONTR 6.53139515 ROUND 7: MAX CORR ( 61.3753712) AFTER KILLING INPUT VARIABLE 3 CONTR 5.4567686 ROUND 8: MAX CORR ( 61.2407259) AFTER KILLING INPUT VARIABLE 13 CONTR 4.06321046 ROUND 9: MAX CORR ( 60.7515609) AFTER KILLING INPUT VARIABLE 9 CONTR 7.72491792 ROUND 10: MAX CORR ( 59.885857) AFTER KILLING INPUT VARIABLE 10 CONTR 10.2194069 ROUND 11: MAX CORR ( 59.0817776) AFTER KILLING INPUT VARIABLE 5 CONTR 9.78056408 ROUND 12: MAX CORR ( 52.6771039) AFTER KILLING INPUT VARIABLE 4 CONTR 26.7540496 LAST REMAINING VARIABLE: 7 total correlation to target: 62.1464047 % total significance: 33.9912351 sigma correlations of single variables to target: variable 2: 53.3375329 % , in sigma: 29.173186 variable 3: 17.7562111 % , in sigma: 9.71183365 variable 4: 47.5295406 % , in sigma: 25.9964804 variable 5: 17.5799972 % , in sigma: 9.61545274 variable 6: 37.2505583 % , in sigma: 20.3743481 variable 7: 52.6771039 % , in sigma: 28.8119615 variable 8: 42.4120451 % , in sigma: 23.1974449 variable 9: 48.3117612 % , in sigma: 26.4243192 variable 10: -29.6062926 % , in sigma: 16.1932852 variable 11: -10.6386168 % , in sigma: 5.81883583 variable 12: -23.6767015 % , in sigma: 12.9500706 variable 13: -0.326558956 % , in sigma: 0.178612782 variable 14: 38.1229313 % , in sigma: 20.8514962 variables sorted by significance: 1 most relevant variable 7 corr 52.6771049 , in sigma: 28.8119621 2 most relevant variable 4 corr 26.7540493 , in sigma: 14.6332388 3 most relevant variable 5 corr 9.78056431 , in sigma: 5.34952042 4 most relevant variable 10 corr 10.2194071 , in sigma: 5.5895473 5 most relevant variable 9 corr 7.72491789 , in sigma: 4.22517604 6 most relevant variable 13 corr 4.06321049 , in sigma: 2.22238991 7 most relevant variable 3 corr 5.45676851 , in sigma: 2.98460228 8 most relevant variable 14 corr 6.53139496 , in sigma: 3.5723737 9 most relevant variable 12 corr 3.82725358 , in sigma: 2.0933323 10 most relevant variable 6 corr 1.89703441 , in sigma: 1.03759088 11 most relevant variable 8 corr 1.75963128 , in sigma: 0.962437661 12 most relevant variable 2 corr 1.04236269 , in sigma: 0.570124618 13 most relevant variable 11 corr 0.61200434 , in sigma: 0.334738325 global correlations between input variables: variable 2: 99.2888071 % variable 3: 90.5729085 % variable 4: 91.2716911 % variable 5: 97.5292672 % variable 6: 95.687306 % variable 7: 99.0993583 % variable 8: 88.1278334 % variable 9: 99.0853622 % variable 10: 72.1211256 % variable 11: 53.0023893 % variable 12: 72.698734 % variable 13: 75.4225842 % variable 14: 87.0848579 % significance loss when removing single variables: variable 2: corr = 1.04740289 % , sigma = 0.572881376 variable 3: corr = 7.51986476 % , sigma = 4.11302138 variable 4: corr = 12.7018182 % , sigma = 6.9473124 variable 5: corr = 9.88934331 % , sigma = 5.40901754 variable 6: corr = 2.49903216 % , sigma = 1.36685606 variable 7: corr = 7.04920522 % , sigma = 3.85559218 variable 8: corr = 2.00319583 % , sigma = 1.09565631 variable 9: corr = 7.12829102 % , sigma = 3.89884848 variable 10: corr = 7.80012452 % , sigma = 4.26631062 variable 11: corr = 0.612004355 % , sigma = 0.334738333 variable 12: corr = 3.78406454 % , sigma = 2.06970987 variable 13: corr = 8.50960729 % , sigma = 4.65436518 variable 14: corr = 6.68319938 % , sigma = 3.65540376 Keep only 5 most significant input variables ------------------------------------- Teacher: actual network topology: Nodes(1) = 6 Nodes(2) = 15 Nodes(3) = 1 ------------------------------------- --------------------------------------------------- Iteration : 1 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 11.0704889 sigma out 15 active outputs RANK 2 NODE 6 --> 7.13495636 sigma out 15 active outputs RANK 3 NODE 2 --> 5.92924166 sigma out 15 active outputs RANK 4 NODE 3 --> 5.8424015 sigma out 15 active outputs RANK 5 NODE 5 --> 5.22543287 sigma out 15 active outputs RANK 6 NODE 4 --> 4.90025377 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 3 --> 9.87181854 sigma in 6act. ( 9.74262142 sig out 1act.) RANK 2 NODE 1 --> 6.94368696 sigma in 6act. ( 7.61627054 sig out 1act.) RANK 3 NODE 15 --> 6.45721817 sigma in 6act. ( 6.31410503 sig out 1act.) RANK 4 NODE 13 --> 5.33976126 sigma in 6act. ( 5.68929768 sig out 1act.) RANK 5 NODE 2 --> 4.93435574 sigma in 6act. ( 4.86611271 sig out 1act.) RANK 6 NODE 12 --> 4.32394314 sigma in 6act. ( 4.19285727 sig out 1act.) RANK 7 NODE 11 --> 3.29466319 sigma in 6act. ( 3.4976933 sig out 1act.) RANK 8 NODE 7 --> 2.80222011 sigma in 6act. ( 2.90283108 sig out 1act.) RANK 9 NODE 4 --> 1.90262794 sigma in 6act. ( 1.930197 sig out 1act.) RANK 10 NODE 14 --> 1.71567786 sigma in 6act. ( 1.62659717 sig out 1act.) RANK 11 NODE 10 --> 1.70998955 sigma in 6act. ( 2.01627469 sig out 1act.) RANK 12 NODE 8 --> 1.58884823 sigma in 6act. ( 1.27671111 sig out 1act.) RANK 13 NODE 9 --> 1.42283118 sigma in 6act. ( 1.1389581 sig out 1act.) RANK 14 NODE 6 --> 1.22714972 sigma in 6act. ( 0.760561109 sig out 1act.) RANK 15 NODE 5 --> 0.948803544 sigma in 6act. ( 0.367847145 sig out 1act.) sorted by output significance RANK 1 NODE 3 --> 9.74262142 sigma out 1act.( 9.87181854 sig in 6act.) RANK 2 NODE 1 --> 7.61627054 sigma out 1act.( 6.94368696 sig in 6act.) RANK 3 NODE 15 --> 6.31410503 sigma out 1act.( 6.45721817 sig in 6act.) RANK 4 NODE 13 --> 5.68929768 sigma out 1act.( 5.33976126 sig in 6act.) RANK 5 NODE 2 --> 4.86611271 sigma out 1act.( 4.93435574 sig in 6act.) RANK 6 NODE 12 --> 4.19285727 sigma out 1act.( 4.32394314 sig in 6act.) RANK 7 NODE 11 --> 3.4976933 sigma out 1act.( 3.29466319 sig in 6act.) RANK 8 NODE 7 --> 2.90283108 sigma out 1act.( 2.80222011 sig in 6act.) RANK 9 NODE 10 --> 2.01627469 sigma out 1act.( 1.70998955 sig in 6act.) RANK 10 NODE 4 --> 1.930197 sigma out 1act.( 1.90262794 sig in 6act.) RANK 11 NODE 14 --> 1.62659717 sigma out 1act.( 1.71567786 sig in 6act.) RANK 12 NODE 8 --> 1.27671111 sigma out 1act.( 1.58884823 sig in 6act.) RANK 13 NODE 9 --> 1.1389581 sigma out 1act.( 1.42283118 sig in 6act.) RANK 14 NODE 6 --> 0.760561109 sigma out 1act.( 1.22714972 sig in 6act.) RANK 15 NODE 5 --> 0.367847145 sigma out 1act.( 0.948803544 sig in 6act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 17.3539467 sigma in 15 active inputs SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 11.5366306 sigma out 15 active outputs RANK 2 NODE 6 --> 10.9378738 sigma out 15 active outputs RANK 3 NODE 3 --> 7.5432272 sigma out 15 active outputs RANK 4 NODE 5 --> 7.45620108 sigma out 15 active outputs RANK 5 NODE 2 --> 6.89960098 sigma out 15 active outputs RANK 6 NODE 4 --> 6.45086622 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 3 --> 9.00550461 sigma in 6act. ( 8.4356041 sig out 1act.) RANK 2 NODE 1 --> 8.41927624 sigma in 6act. ( 8.31106663 sig out 1act.) RANK 3 NODE 12 --> 7.29127073 sigma in 6act. ( 4.0495739 sig out 1act.) RANK 4 NODE 2 --> 7.01575756 sigma in 6act. ( 5.5341053 sig out 1act.) RANK 5 NODE 15 --> 5.88350296 sigma in 6act. ( 7.19433832 sig out 1act.) RANK 6 NODE 6 --> 5.7906127 sigma in 6act. ( 2.87555265 sig out 1act.) RANK 7 NODE 13 --> 5.38182116 sigma in 6act. ( 4.54990625 sig out 1act.) RANK 8 NODE 11 --> 5.01030064 sigma in 6act. ( 4.00689888 sig out 1act.) RANK 9 NODE 9 --> 4.49787092 sigma in 6act. ( 2.92175221 sig out 1act.) RANK 10 NODE 10 --> 4.45945978 sigma in 6act. ( 3.39249778 sig out 1act.) RANK 11 NODE 4 --> 3.71185327 sigma in 6act. ( 2.70117354 sig out 1act.) RANK 12 NODE 14 --> 3.08699894 sigma in 6act. ( 1.2237972 sig out 1act.) RANK 13 NODE 8 --> 2.27737951 sigma in 6act. ( 0.432032466 sig out 1act.) RANK 14 NODE 5 --> 2.16668892 sigma in 6act. ( 0.433076978 sig out 1act.) RANK 15 NODE 7 --> 2.13484192 sigma in 6act. ( 1.1803385 sig out 1act.) sorted by output significance RANK 1 NODE 3 --> 8.4356041 sigma out 1act.( 9.00550461 sig in 6act.) RANK 2 NODE 1 --> 8.31106663 sigma out 1act.( 8.41927624 sig in 6act.) RANK 3 NODE 15 --> 7.19433832 sigma out 1act.( 5.88350296 sig in 6act.) RANK 4 NODE 2 --> 5.5341053 sigma out 1act.( 7.01575756 sig in 6act.) RANK 5 NODE 13 --> 4.54990625 sigma out 1act.( 5.38182116 sig in 6act.) RANK 6 NODE 12 --> 4.0495739 sigma out 1act.( 7.29127073 sig in 6act.) RANK 7 NODE 11 --> 4.00689888 sigma out 1act.( 5.01030064 sig in 6act.) RANK 8 NODE 10 --> 3.39249778 sigma out 1act.( 4.45945978 sig in 6act.) RANK 9 NODE 9 --> 2.92175221 sigma out 1act.( 4.49787092 sig in 6act.) RANK 10 NODE 6 --> 2.87555265 sigma out 1act.( 5.7906127 sig in 6act.) RANK 11 NODE 4 --> 2.70117354 sigma out 1act.( 3.71185327 sig in 6act.) RANK 12 NODE 14 --> 1.2237972 sigma out 1act.( 3.08699894 sig in 6act.) RANK 13 NODE 7 --> 1.1803385 sigma out 1act.( 2.13484192 sig in 6act.) RANK 14 NODE 5 --> 0.433076978 sigma out 1act.( 2.16668892 sig in 6act.) RANK 15 NODE 8 --> 0.432032466 sigma out 1act.( 2.27737951 sig in 6act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 17.7383728 sigma in 15 active inputs *********************************************** *** Learn Path 1 *** loss function: -0.425129712 *** contribution from regularisation: 0.0179043729 *** contribution from error: -0.443034083 *********************************************** -----------------> Test sample --------------------------------------------------- Iteration : 2 *********************************************** *** Learn Path 2 *** loss function: -0.513302982 *** contribution from regularisation: 0.00982023403 *** contribution from error: -0.523123205 *********************************************** -----------------> Test sample ENTER BFGS code START -4435.28831 -0.252557069 -0.0738264024 EXIT FROM BFGS code FG_START 0. -0.252557069 0. --------------------------------------------------- Iteration : 3 *********************************************** *** Learn Path 3 *** loss function: -0.536929786 *** contribution from regularisation: 0.00580768846 *** contribution from error: -0.542737484 *********************************************** -----------------> Test sample ENTER BFGS code FG_START -4638.53625 -0.252557069 -26.6275673 EXIT FROM BFGS code FG_LNSRCH 0. -0.339364648 0. --------------------------------------------------- Iteration : 4 *********************************************** *** Learn Path 4 *** loss function: -0.561105371 *** contribution from regularisation: 0.0100447517 *** contribution from error: -0.571150124 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4847.38914 -0.339364648 13.0462713 EXIT FROM BFGS code NEW_X -4847.38914 -0.339364648 13.0462713 ENTER BFGS code NEW_X -4847.38914 -0.339364648 13.0462713 EXIT FROM BFGS code FG_LNSRCH 0. -0.313043654 0. --------------------------------------------------- Iteration : 5 *********************************************** *** Learn Path 5 *** loss function: -0.56335032 *** contribution from regularisation: 0.0111163864 *** contribution from error: -0.574466705 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4866.78364 -0.313043654 -3.62422848 EXIT FROM BFGS code NEW_X -4866.78364 -0.313043654 -3.62422848 ENTER BFGS code NEW_X -4866.78364 -0.313043654 -3.62422848 EXIT FROM BFGS code FG_LNSRCH 0. -0.318820477 0. --------------------------------------------------- Iteration : 6 *********************************************** *** Learn Path 6 *** loss function: -0.564056218 *** contribution from regularisation: 0.0106104389 *** contribution from error: -0.574666679 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4872.88177 -0.318820477 -2.54459286 EXIT FROM BFGS code FG_LNSRCH 0. -0.341927797 0. --------------------------------------------------- Iteration : 7 *********************************************** *** Learn Path 7 *** loss function: -0.564145327 *** contribution from regularisation: 0.0104360636 *** contribution from error: -0.574581385 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4873.65153 -0.341927797 2.45238948 EXIT FROM BFGS code NEW_X -4873.65153 -0.341927797 2.45238948 ENTER BFGS code NEW_X -4873.65153 -0.341927797 2.45238948 EXIT FROM BFGS code FG_LNSRCH 0. -0.367923319 0. --------------------------------------------------- Iteration : 8 *********************************************** *** Learn Path 8 *** loss function: -0.565230608 *** contribution from regularisation: 0.00906621851 *** contribution from error: -0.574296832 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4883.02735 -0.367923319 8.75308037 EXIT FROM BFGS code NEW_X -4883.02735 -0.367923319 8.75308037 ENTER BFGS code NEW_X -4883.02735 -0.367923319 8.75308037 EXIT FROM BFGS code FG_LNSRCH 0. -0.402691036 0. --------------------------------------------------- Iteration : 9 *********************************************** *** Learn Path 9 *** loss function: -0.553587854 *** contribution from regularisation: 0.0103593785 *** contribution from error: -0.56394726 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4782.44523 -0.402691036 17.7583008 EXIT FROM BFGS code FG_LNSRCH 0. -0.37639299 0. --------------------------------------------------- Iteration : 10 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 12.8884344 sigma out 15 active outputs RANK 2 NODE 6 --> 11.697464 sigma out 15 active outputs RANK 3 NODE 3 --> 4.10206461 sigma out 15 active outputs RANK 4 NODE 5 --> 2.75993705 sigma out 15 active outputs RANK 5 NODE 4 --> 2.56188798 sigma out 15 active outputs RANK 6 NODE 2 --> 1.70524096 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 6 --> 9.6360569 sigma in 6act. ( 6.38323259 sig out 1act.) RANK 2 NODE 2 --> 7.02747869 sigma in 6act. ( 5.15993309 sig out 1act.) RANK 3 NODE 9 --> 6.59005499 sigma in 6act. ( 4.62930346 sig out 1act.) RANK 4 NODE 10 --> 6.53551722 sigma in 6act. ( 4.10201311 sig out 1act.) RANK 5 NODE 4 --> 5.05429316 sigma in 6act. ( 3.47292805 sig out 1act.) RANK 6 NODE 15 --> 4.63349485 sigma in 6act. ( 2.80119896 sig out 1act.) RANK 7 NODE 1 --> 4.20726633 sigma in 6act. ( 1.91731 sig out 1act.) RANK 8 NODE 11 --> 3.5377264 sigma in 6act. ( 2.05997396 sig out 1act.) RANK 9 NODE 3 --> 3.18306494 sigma in 6act. ( 2.203722 sig out 1act.) RANK 10 NODE 12 --> 3.01728153 sigma in 6act. ( 1.60300136 sig out 1act.) RANK 11 NODE 14 --> 1.99644482 sigma in 6act. ( 0.91043067 sig out 1act.) RANK 12 NODE 5 --> 1.89685905 sigma in 6act. ( 1.20381069 sig out 1act.) RANK 13 NODE 13 --> 1.77595615 sigma in 6act. ( 0.603057563 sig out 1act.) RANK 14 NODE 7 --> 0.875624955 sigma in 6act. ( 0.611351311 sig out 1act.) RANK 15 NODE 8 --> 0.710338056 sigma in 6act. ( 0.252362132 sig out 1act.) sorted by output significance RANK 1 NODE 6 --> 6.38323259 sigma out 1act.( 9.6360569 sig in 6act.) RANK 2 NODE 2 --> 5.15993309 sigma out 1act.( 7.02747869 sig in 6act.) RANK 3 NODE 9 --> 4.62930346 sigma out 1act.( 6.59005499 sig in 6act.) RANK 4 NODE 10 --> 4.10201311 sigma out 1act.( 6.53551722 sig in 6act.) RANK 5 NODE 4 --> 3.47292805 sigma out 1act.( 5.05429316 sig in 6act.) RANK 6 NODE 15 --> 2.80119896 sigma out 1act.( 4.63349485 sig in 6act.) RANK 7 NODE 3 --> 2.203722 sigma out 1act.( 3.18306494 sig in 6act.) RANK 8 NODE 11 --> 2.05997396 sigma out 1act.( 3.5377264 sig in 6act.) RANK 9 NODE 1 --> 1.91731 sigma out 1act.( 4.20726633 sig in 6act.) RANK 10 NODE 12 --> 1.60300136 sigma out 1act.( 3.01728153 sig in 6act.) RANK 11 NODE 5 --> 1.20381069 sigma out 1act.( 1.89685905 sig in 6act.) RANK 12 NODE 14 --> 0.91043067 sigma out 1act.( 1.99644482 sig in 6act.) RANK 13 NODE 7 --> 0.611351311 sigma out 1act.( 0.875624955 sig in 6act.) RANK 14 NODE 13 --> 0.603057563 sigma out 1act.( 1.77595615 sig in 6act.) RANK 15 NODE 8 --> 0.252362132 sigma out 1act.( 0.710338056 sig in 6act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 11.9983425 sigma in 15 active inputs *********************************************** *** Learn Path 10 *** loss function: -0.564813077 *** contribution from regularisation: 0.00919685885 *** contribution from error: -0.574009955 *********************************************** -----------------> Test sample Iteration No: 10 ********************************************** ***** write out current network **** ***** to "rescue.nb" **** ********************************************** SAVING EXPERTISE TO rescue.nb ENTER BFGS code FG_LNSRCH -4879.41994 -0.37639299 12.2870693 EXIT FROM BFGS code FG_LNSRCH 0. -0.369654447 0. --------------------------------------------------- Iteration : 11 *********************************************** *** Learn Path 11 *** loss function: -0.562047362 *** contribution from regularisation: 0.0122274607 *** contribution from error: -0.574274838 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4855.52695 -0.369654447 9.28404331 EXIT FROM BFGS code FG_LNSRCH 0. -0.367969364 0. --------------------------------------------------- Iteration : 12 *********************************************** *** Learn Path 12 *** loss function: -0.564290106 *** contribution from regularisation: 0.0100063607 *** contribution from error: -0.574296474 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4874.9022 -0.367969364 8.41549397 EXIT FROM BFGS code FG_LNSRCH 0. -0.367923439 0. --------------------------------------------------- Iteration : 13 *********************************************** *** Learn Path 13 *** loss function: -0.564435184 *** contribution from regularisation: 0.00986169558 *** contribution from error: -0.574296892 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4876.15548 -0.367923439 8.58274555 EXIT FROM BFGS code FG_LNSRCH 0. -0.367923319 0. --------------------------------------------------- Iteration : 14 *********************************************** *** Learn Path 14 *** loss function: -0.564024508 *** contribution from regularisation: 0.0102723092 *** contribution from error: -0.574296832 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4872.60794 -0.367923319 8.42241192 EXIT FROM BFGS code FG_LNSRCH 0. -0.367923319 0. --------------------------------------------------- Iteration : 15 *********************************************** *** Learn Path 15 *** loss function: -0.564220011 *** contribution from regularisation: 0.0100768059 *** contribution from error: -0.574296832 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4874.29689 -0.367923319 8.56901169 EXIT FROM BFGS code FG_LNSRCH 0. -0.367923319 0. --------------------------------------------------- Iteration : 16 *********************************************** *** Learn Path 16 *** loss function: -0.563868046 *** contribution from regularisation: 0.0104287704 *** contribution from error: -0.574296832 *********************************************** -----------------> Test sample ENTER BFGS code FG_LNSRCH -4871.25627 -0.367923319 8.37780285 EXIT FROM BFGS code NEW_X -4871.25627 -0.367923319 8.37780285 ENTER BFGS code NEW_X -4871.25627 -0.367923319 8.37780285 EXIT FROM BFGS code CONVERGENC -4871.25627 -0.367923319 8.37780285 --------------------------------------------------- Iteration : 250 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 19.3169937 sigma out 15 active outputs RANK 2 NODE 6 --> 17.7350807 sigma out 15 active outputs RANK 3 NODE 3 --> 6.30487919 sigma out 15 active outputs RANK 4 NODE 5 --> 4.83298969 sigma out 15 active outputs RANK 5 NODE 4 --> 4.15433455 sigma out 15 active outputs RANK 6 NODE 2 --> 3.38988805 sigma out 15 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 6 --> 15.3618336 sigma in 6act. ( 9.59956455 sig out 1act.) RANK 2 NODE 2 --> 10.1958294 sigma in 6act. ( 8.00893307 sig out 1act.) RANK 3 NODE 9 --> 9.97274113 sigma in 6act. ( 7.4600029 sig out 1act.) RANK 4 NODE 10 --> 9.83201599 sigma in 6act. ( 6.32345247 sig out 1act.) RANK 5 NODE 4 --> 7.10041666 sigma in 6act. ( 5.78862476 sig out 1act.) RANK 6 NODE 15 --> 6.94911861 sigma in 6act. ( 5.10893202 sig out 1act.) RANK 7 NODE 1 --> 6.27500057 sigma in 6act. ( 4.36647129 sig out 1act.) RANK 8 NODE 11 --> 5.26404572 sigma in 6act. ( 3.62294936 sig out 1act.) RANK 9 NODE 12 --> 5.25537777 sigma in 6act. ( 3.9962244 sig out 1act.) RANK 10 NODE 3 --> 5.14097548 sigma in 6act. ( 4.95642471 sig out 1act.) RANK 11 NODE 13 --> 2.69871759 sigma in 6act. ( 1.49943042 sig out 1act.) RANK 12 NODE 5 --> 2.65930462 sigma in 6act. ( 1.81868696 sig out 1act.) RANK 13 NODE 14 --> 2.50566435 sigma in 6act. ( 1.67026699 sig out 1act.) RANK 14 NODE 8 --> 1.25916576 sigma in 6act. ( 0.421952873 sig out 1act.) RANK 15 NODE 7 --> 1.18916392 sigma in 6act. ( 0.776568055 sig out 1act.) sorted by output significance RANK 1 NODE 6 --> 9.59956455 sigma out 1act.( 15.3618336 sig in 6act.) RANK 2 NODE 2 --> 8.00893307 sigma out 1act.( 10.1958294 sig in 6act.) RANK 3 NODE 9 --> 7.4600029 sigma out 1act.( 9.97274113 sig in 6act.) RANK 4 NODE 10 --> 6.32345247 sigma out 1act.( 9.83201599 sig in 6act.) RANK 5 NODE 4 --> 5.78862476 sigma out 1act.( 7.10041666 sig in 6act.) RANK 6 NODE 15 --> 5.10893202 sigma out 1act.( 6.94911861 sig in 6act.) RANK 7 NODE 3 --> 4.95642471 sigma out 1act.( 5.14097548 sig in 6act.) RANK 8 NODE 1 --> 4.36647129 sigma out 1act.( 6.27500057 sig in 6act.) RANK 9 NODE 12 --> 3.9962244 sigma out 1act.( 5.25537777 sig in 6act.) RANK 10 NODE 11 --> 3.62294936 sigma out 1act.( 5.26404572 sig in 6act.) RANK 11 NODE 5 --> 1.81868696 sigma out 1act.( 2.65930462 sig in 6act.) RANK 12 NODE 14 --> 1.67026699 sigma out 1act.( 2.50566435 sig in 6act.) RANK 13 NODE 13 --> 1.49943042 sigma out 1act.( 2.69871759 sig in 6act.) RANK 14 NODE 7 --> 0.776568055 sigma out 1act.( 1.18916392 sig in 6act.) RANK 15 NODE 8 --> 0.421952873 sigma out 1act.( 1.25916576 sig in 6act.) SIGNIFICANCE OF INPUTS TO LAYER 3 RANK 1 NODE 1 --> 19.8342209 sigma in 15 active inputs *********************************************** *** Learn Path 250 *** loss function: -0.564048529 *** contribution from regularisation: 0.0102483211 *** contribution from error: -0.574296832 *********************************************** -----------------> Test sample END OF LEARNING , export EXPERTISE SAVING EXPERTISE TO expert.nb NB_AHISTOUT: storage space 23570 Closing output file done