Training in /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream Network Config file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/GlobalPID_Muon_Upstream_ANN.txt Training parameters file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/train-config.txt Input Data file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/datafiles.txt Neurobayes parameters file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/NB.txt Training Host = lxplus432.cern.ch Particle type = muon Background types = all Training Mix = NaturalMix Track type = Upstream Track PresSel = TrackPreSelNone Network type = NeuroBayes Ghost treatment = Ghosts Ghosts Min P = 0 MeV/c Min Pt = 0 MeV/c Max Chi^2 = 10 Min likelihood = -100 Max Ghost Prob = 1 Output file = GlobalPID_Muon_Upstream_NeuroBayes.conf Skipping input #RichUsedR2Gas Skipping input #RichAboveElThres Skipping input #RichAbovePiThres Skipping input #RichAbovePrThres Training ROOT file /castor/cern.ch/user/j/jonrob/ProtoParticlePIDtuples/MC12-Binc-nu2.5/Reco13d.root Evaluation ROOT file /castor/cern.ch/user/j/jonrob/ProtoParticlePIDtuples/MC12-Binc-nu2.5/Reco13a.root Training sample size = 1000000 Evaluation sample size = 5000000 Node layer two scale = 1.2 Input layer has 23 nodes, hidden layer has 26 nodes NB_DEF_TASK = CLA NB_DEF_MOM = 0 NB_DEF_REG = ALL NB_DEF_LOSS = ENTROPY NB_DEF_METHOD = BFGS NB_DEF_SHAPE = DIAG NB_DEF_LEARNDIAG = 1 NB_DEF_PRE = 621 ********************************************* * This product is licenced for educational * * and scientific use only. Commercial use * * is prohibited ! * ********************************************* Your number of nodes in the input layer is: 23 Your number of nodes in the hidden layer is: 26 Your number of nodes in the output layer is: 1 You want to do classification You want to fix prepro shape to 6. order (DIA) and transform each node to diagonal You want to use fit alternative 2 for diag fit You use ASR+ARD for regularisation You use entropy as a loss function You want to use the BFGS algorithm You want to include the deviation from the diagonal in the error function global preprocessing flag: 621 You want to use the global preprocessing flag 21 You use momentum: 0.0000000 Input 2 NumProtoParticles PreproFlag 19 Input 3 TrackP PreproFlag 34 Input 4 TrackPt PreproFlag 34 Input 5 TrackChi2PerDof PreproFlag 14 Input 6 TrackNumDof PreproFlag 19 Input 7 TrackLikelihood PreproFlag 34 Input 8 TrackGhostProbability PreproFlag 34 Input 9 TrackCloneDist PreproFlag 34 Input 10 TrackFitVeloChi2 PreproFlag 14 Input 11 TrackFitVeloNDoF PreproFlag 19 Input 12 RichUsedAero PreproFlag 18 Input 13 RichUsedR1Gas PreproFlag 18 Input 14 RichAboveMuThres PreproFlag 18 Input 15 RichAboveKaThres PreproFlag 18 Input 16 RichDLLe PreproFlag 34 Input 17 RichDLLmu PreproFlag 34 Input 18 RichDLLk PreproFlag 34 Input 19 RichDLLp PreproFlag 34 Input 20 RichDLLbt PreproFlag 34 Input 21 InAccBrem PreproFlag 19 Input 22 BremPIDe PreproFlag 34 Input 23 VeloCharge PreproFlag 34 Attempting to open training ROOT file /castor/cern.ch/user/j/jonrob/ProtoParticlePIDtuples/MC12-Binc-nu2.5/Reco13d.root Found 5016459 training data points Read entry 501645 (9.99998%) Read entry 1003290 (20%) Read entry 1504935 (29.9999%) Read entry 2006580 (39.9999%) Read entry 2508225 (49.9999%) Read entry 3009870 (59.9999%) Read entry 3511515 (69.9999%) Read entry 4013160 (79.9999%) Read entry 4514805 (89.9998%) Read entry 5016450 (99.9998%) Considered 5016459 tracks for input to NN training Sel. Eff. = 15.3957% Selected 772320 tracks for input to NN training ghost percentage = 31.254% electron percentage = 4.90095% muon percentage = 0.306868% pion percentage = 53.4443% kaon percentage = 7.06508% Unknown Particle type 411 percentage = 0.00038844% Unknown Particle type 431 percentage = 0.00012948% Unknown Particle type 521 percentage = 0.00012948% proton percentage = 2.93674% Unknown Particle type 3112 percentage = 0.0337943% Unknown Particle type 3222 percentage = 0.0280972% Unknown Particle type 3312 percentage = 0.0130775% Unknown Particle type 3334 percentage = 0.00077688% Unknown Particle type 1000010020 percentage = 0.00246012% Unknown Particle type 1000010030 percentage = 0.00297804% Unknown Particle type 1000020040 percentage = 0.0102289% Starting Training. << 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 GmbH 2001-2011 Copyright Phi-T GmbH Version 20120322 Library compiled with: Number of Events= 772320 NB_MAXNODE = 150 ----------------------------------- preprocessing flags/parameters: individual preprocessing: variable # 2 : PreproFlag = 19 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 3 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 4 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 5 : PreproFlag = 14 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 6 : PreproFlag = 19 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 7 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 8 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 9 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 10 : PreproFlag = 14 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 11 : PreproFlag = 19 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 12 : PreproFlag = 18 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 13 : PreproFlag = 18 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 14 : PreproFlag = 18 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 15 : PreproFlag = 18 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 16 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 17 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 18 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 19 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 20 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 21 : PreproFlag = 19 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 22 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 variable # 23 : PreproFlag = 34 parameter # 1 = 0.0000000 parameter # 2 = 0.0000000 parameter # 3 = 0.0000000 parameter # 4 = 0.0000000 parameter # 5 = 0.0000000 parameter # 6 = 0.0000000 parameter # 7 = 0.0000000 parameter # 8 = 0.0000000 parameter # 9 = 0.0000000 parameter # 10 = 0.0000000 Using weight factor: 1.00000000000000000 now perform preprocessing *** called with option 21 *** This will do for you: *** input variable equalisation *** to flat distribution with mean=0 and sigma=1 *** Then variables are decorrelated *** and rotated that all correlation to performance is in 2. input node Signal fraction: 0.30686763 % ------------------------------ Transdef: Tab for variable 1 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 -1.00000000 1.00000000 ------------------------------ Transdef: Tab for variable 2 4.0000000 25.000000 29.000000 33.000000 35.000000 37.000000 39.000000 41.000000 43.000000 44.000000 46.000000 47.000000 49.000000 50.000000 51.000000 52.000000 53.000000 55.000000 56.000000 57.000000 58.000000 59.000000 60.000000 61.000000 62.000000 63.000000 64.000000 65.000000 66.000000 67.000000 68.000000 69.000000 70.000000 71.000000 72.000000 73.000000 74.000000 75.000000 76.000000 77.000000 78.000000 79.000000 80.000000 81.000000 81.000000 82.000000 83.000000 84.000000 85.000000 86.000000 87.000000 88.000000 89.000000 90.000000 91.000000 92.000000 93.000000 94.000000 95.000000 96.000000 97.000000 98.000000 99.000000 101.00000 102.00000 103.00000 104.00000 105.00000 106.00000 108.00000 109.00000 110.00000 111.00000 113.00000 114.00000 115.00000 117.00000 118.00000 120.00000 121.00000 123.00000 125.00000 126.00000 128.00000 130.00000 132.00000 135.00000 137.00000 139.00000 142.00000 145.00000 149.00000 152.00000 156.00000 161.00000 166.00000 173.00000 181.00000 191.00000 209.00000 407.00000 build map for variable # 2 NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 206.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 207.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 208.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 209.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 210.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 225.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 226.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 227.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 228.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 241.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 242.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 243.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 244.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 245.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 246.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 247.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 248.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 249.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 250.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 251.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 252.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 253.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 254.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 270.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 271.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 272.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 273.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 274.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 276.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 277.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 278.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 279.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 280.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 281.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 282.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 283.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 284.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 286.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 287.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 288.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 289.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 290.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 291.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 292.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 295.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 296.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 297.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 298.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 299.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 300.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 302.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 303.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 304.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 305.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 306.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 307.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 308.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 309.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 310.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 312.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 313.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 317.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 318.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 319.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 320.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 323.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 325.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 326.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 331.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 339.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 341.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 345.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 347.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 348.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 349.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 351.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 354.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 355.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 356.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 358.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 360.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 370.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 371.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 375.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 383.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 386.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 387.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 390.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 394.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 403.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 404.00000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 2 for key 407.00000 Unregularised mean is returned ------------------------------ Transdef: Tab for variable 3 226.37000 514.89502 567.52002 607.59998 640.98499 670.82001 698.53003 724.23999 748.34998 771.37000 793.32001 814.52002 835.53003 856.29999 876.76501 896.95001 916.78998 936.46997 956.15997 975.45001 995.06000 1014.5350 1034.2500 1053.8800 1073.6851 1093.2300 1112.8300 1132.8101 1152.7800 1173.1899 1193.1550 1213.2300 1233.1899 1254.0000 1274.9900 1295.9650 1317.4700 1339.4200 1361.8700 1383.6899 1406.3149 1429.4550 1452.9750 1476.8450 1501.2400 1525.8900 1551.4700 1577.5601 1604.3199 1631.2300 1659.3600 1687.8600 1717.4800 1747.9301 1778.6300 1810.3300 1842.8700 1876.9050 1910.9850 1947.4399 1984.9150 2023.9700 2064.2300 2106.4500 2150.2000 2196.1348 2243.0701 2294.2300 2347.0400 2403.9751 2464.4551 2527.4199 2595.6548 2669.1499 2749.4099 2833.5049 2924.7000 3025.0801 3135.4448 3253.9299 3388.4751 3536.7949 3711.7200 3906.8799 4129.6201 4388.4648 4688.2998 5046.8550 5474.4102 5988.2646 6607.2148 7349.1299 8275.8398 9423.2793 10873.075 12690.450 15085.064 18350.871 23629.789 35141.703 4840366.5 do regularised spline fit for input variable # 3 build map for variable # 3 warning: map is empty for variable 3 ------------------------------ Transdef: Tab for variable 4 0.71040547 18.998266 25.029394 29.817083 34.086815 38.072899 41.942284 45.705200 49.357372 52.998123 56.581856 60.127853 63.595406 67.075806 70.571953 74.110985 77.641495 81.217491 84.853622 88.536903 92.305420 96.042892 99.765694 103.59299 107.45895 111.32054 115.20042 119.09923 123.19179 127.20603 131.27023 135.38664 139.47900 143.71446 147.91742 152.23279 156.59637 160.95825 165.40314 169.93593 174.51526 179.09683 183.72760 188.37357 193.06277 197.90239 202.71222 207.66299 212.73906 217.93939 223.17793 228.46497 233.81461 239.26770 244.82269 250.54233 256.52286 262.50067 268.62689 274.97107 281.52341 288.17010 294.92975 301.88824 309.08896 316.53198 324.11035 332.10022 340.21954 348.55649 357.18561 366.26111 375.77228 385.39844 395.55188 405.84048 416.58121 427.91010 439.94193 452.57166 465.98080 479.58655 494.59448 510.24969 527.57861 546.09033 566.93030 589.25049 614.06323 641.27209 672.12543 708.62927 750.16937 799.88269 860.72363 939.30994 1044.4626 1200.3441 1469.8967 2150.4204 994541.06 do regularised spline fit for input variable # 4 build map for variable # 4 warning: map is empty for variable 4 ------------------------------ Transdef: Tab for variable 5 3.05519532E-03 0.15486994 0.20630372 0.24315959 0.27337432 0.30026203 0.32476443 0.34690422 0.36744100 0.38692361 0.40532398 0.42251408 0.43935937 0.45539698 0.47130072 0.48649335 0.50127321 0.51580238 0.52980244 0.54394293 0.55775058 0.57140785 0.58497971 0.59820473 0.61115426 0.62423861 0.63698518 0.64974916 0.66250730 0.67516017 0.68795729 0.70060635 0.71337962 0.72582728 0.73843944 0.75074714 0.76312411 0.77558237 0.78797734 0.80024803 0.81322563 0.82592976 0.83863592 0.85121268 0.86405885 0.87689495 0.89006507 0.90322769 0.91643733 0.92956924 0.94292152 0.95671916 0.97080553 0.98476946 0.99893004 1.0130451 1.0276854 1.0421243 1.0569758 1.0720754 1.0874982 1.1033230 1.1195015 1.1359428 1.1526418 1.1695535 1.1868864 1.2045417 1.2229257 1.2419071 1.2612002 1.2809125 1.3014629 1.3222556 1.3435241 1.3660579 1.3888900 1.4124186 1.4369431 1.4627891 1.4903271 1.5190074 1.5488577 1.5800207 1.6137779 1.6482010 1.6853607 1.7257160 1.7679839 1.8142285 1.8633366 1.9160552 1.9744887 2.0399737 2.1100893 2.1905642 2.2802866 2.3865786 2.5134978 2.6797657 2.9985514 do regularised spline fit for input variable # 5 ------------------------------ Transdef: Tab for variable 6 4.0000000 4.0000000 4.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 10.0000000 10.0000000 10.0000000 10.0000000 10.0000000 10.0000000 10.0000000 10.0000000 10.0000000 11.000000 11.000000 11.000000 11.000000 11.000000 11.000000 11.000000 11.000000 11.000000 11.000000 12.000000 12.000000 12.000000 12.000000 12.000000 12.000000 12.000000 13.000000 13.000000 13.000000 13.000000 13.000000 13.000000 13.000000 14.000000 14.000000 14.000000 14.000000 15.000000 15.000000 15.000000 15.000000 16.000000 17.000000 18.000000 29.000000 build map for variable # 6 NB_MapRegMean: WARNING Variance of mean targets is zero in map id 6 for key 24.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 6 for key 25.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 6 for key 26.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 6 for key 28.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 6 for key 29.000000 Unregularised mean is returned ------------------------------ Transdef: Tab for variable 7 -99.187744 -27.266464 -20.046114 -15.731812 -13.380541 -11.984915 -11.009474 -10.259741 -9.6652985 -9.1762085 -8.7625189 -8.3921413 -8.0755653 -7.7974043 -7.5282917 -7.2755928 -7.0408688 -6.8192844 -6.6155849 -6.4304142 -6.2515001 -6.0819473 -5.9281950 -5.7788062 -5.6394486 -5.5060825 -5.3835254 -5.2641950 -5.1482034 -5.0292120 -4.9103227 -4.8016701 -4.6987820 -4.6043777 -4.5160208 -4.4351606 -4.3553858 -4.2796073 -4.2049952 -4.1300001 -4.0513115 -3.9675169 -3.8804135 -3.7928441 -3.7067008 -3.6243744 -3.5439773 -3.4647288 -3.3862047 -3.3064830 -3.2245917 -3.1432848 -3.0647554 -2.9937158 -2.9256425 -2.8614259 -2.8001866 -2.7393394 -2.6804075 -2.6209617 -2.5617986 -2.5028248 -2.4462311 -2.3928640 -2.3419566 -2.2939243 -2.2476139 -2.2043509 -2.1611900 -2.1189251 -2.0770741 -2.0357213 -1.9946733 -1.9518496 -1.9105344 -1.8695724 -1.8275788 -1.7872380 -1.7441918 -1.7018530 -1.6601105 -1.6176342 -1.5765326 -1.5359625 -1.4971771 -1.4596143 -1.4227855 -1.3874848 -1.3535397 -1.3197353 -1.2855923 -1.2532527 -1.2210244 -1.1848173 -1.1502988 -1.1164100 -1.0746772 -1.0355000 -0.98853946 -0.92018878 -0.32560724 do regularised spline fit for input variable # 7 build map for variable # 7 warning: map is empty for variable 7 ------------------------------ Transdef: Tab for variable 8 3.63154449E-02 8.18078369E-02 9.07289013E-02 9.67641175E-02 0.10149342 0.10547756 0.10895796 0.11207633 0.11496192 0.11765009 0.12020374 0.12261231 0.12487165 0.12704608 0.12912017 0.13113794 0.13309544 0.13499880 0.13689144 0.13872489 0.14056955 0.14235207 0.14415494 0.14595461 0.14772221 0.14953151 0.15129697 0.15309390 0.15489116 0.15670386 0.15849975 0.16035163 0.16219620 0.16405040 0.16596648 0.16789414 0.16988753 0.17187987 0.17394674 0.17603061 0.17822528 0.18043828 0.18274054 0.18512790 0.18762021 0.19018272 0.19285876 0.19562569 0.19858569 0.20167726 0.20486522 0.20815679 0.21171716 0.21543467 0.21942458 0.22366284 0.22820657 0.23306689 0.23825935 0.24378374 0.24969476 0.25607640 0.26299632 0.27044523 0.27857143 0.28683674 0.29592073 0.30513144 0.31473631 0.32433611 0.33401260 0.34353340 0.35300383 0.36235642 0.37145567 0.38071653 0.38967049 0.39851546 0.40753442 0.41639581 0.42548072 0.43507990 0.44481048 0.45499930 0.46538335 0.47652495 0.48840731 0.50092816 0.51400805 0.52817369 0.54333872 0.55914283 0.57663459 0.59573150 0.61678767 0.64013350 0.66789353 0.69970506 0.73912346 0.79538292 0.99986547 do regularised spline fit for input variable # 8 build map for variable # 8 warning: map is empty for variable 8 ------------------------------ Transdef: Tab for variable 9 2.2737811 33.404442 58.123322 80.774399 100.05792 121.34120 138.80321 159.85948 180.46027 199.52338 220.36038 240.98761 261.43091 283.30823 310.45160 334.90228 361.51050 392.50977 422.16190 450.42505 485.75958 521.31128 555.50189 593.92847 634.05115 677.15112 720.93311 765.18872 812.04401 858.35706 901.84619 949.66785 996.15588 1039.1780 1079.4380 1124.0852 1168.3096 1216.8497 1262.0879 1308.3550 1353.1465 1395.1035 1439.3914 1486.4800 1530.3530 1576.0990 1622.4873 1667.9174 1713.6528 1758.1792 1805.7356 1857.1125 1905.7891 1948.6799 1997.3103 2049.1909 2104.8845 2151.8218 2205.85 Only one class left for trimmed mean or sigma very small -> take "normal" mean 79 2254.9727 2308.3706 2367.6553 2425.7158 2487.6084 2543.0371 2601.8223 2656.8818 2719.6021 2772.9517 2827.1387 2893.1919 2961.3787 3025.2935 3083.8970 3142.5059 3211.7539 3266.4583 3343.2192 3408.5522 3471.1370 3544.3318 3619.3164 3686.0386 3761.5156 3833.4548 3908.6104 3983.9521 4053.8555 4123.9395 4199.4785 4271.3896 4335.5127 4409.0977 4482.5444 4555.0405 4622.3662 4711.6445 4779.1362 4847.2383 4921.6904 4999.4873 do regularised spline fit for input variable # 9 build map for variable # 9 ------------------------------ Transdef: Tab for variable 10 5.74890291E-05 0.12881958 0.24534276 0.35734957 0.46685642 0.57293761 0.67726338 0.77559114 0.87346166 0.97296906 1.0692642 1.1651018 1.2602211 1.3551965 1.4524658 1.5457470 1.6401057 1.7322466 1.8245221 1.9182050 2.0115001 2.1033077 2.1958101 2.2903755 2.3837748 2.4763179 2.5709383 2.6679668 2.7623343 2.8573651 2.9524863 3.0498266 3.1464190 3.2426679 3.3404722 3.4389796 3.5366771 3.6358407 3.7355866 3.8373220 3.9394701 4.0418634 4.1461611 4.2489924 4.3528337 4.4589095 4.5656271 4.6756597 4.7866726 4.8967099 5.0103006 5.1258640 5.2421160 5.3612309 5.4796147 5.5997915 5.7217531 5.8467445 5.9722385 6.0984678 6.2274876 6.3575368 6.4925642 6.6297779 6.7697182 6.9116678 7.0563555 7.2065811 7.3573732 7.5071726 7.6662107 7.8269424 7.9911675 8.1615734 8.3335533 8.5152206 8.7001419 8.8956127 9.0946732 9.3038635 9.5201674 9.7447453 9.9737606 10.213985 10.467916 10.731649 11.018169 11.317972 11.647563 11.989166 12.359715 12.773058 13.222935 13.735571 14.320901 14.990686 15.798859 16.817493 18.195459 20.523954 48.505966 do regularised spline fit for input variable # 10 ------------------------------ Transdef: Tab for variable 11 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 2.0000000 2.0000000 2.0000000 2.0000000 2.0000000 2.0000000 2.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 3.0000000 4.0000000 4.0000000 4.0000000 4.0000000 4.0000000 4.0000000 4.0000000 4.0000000 4.0000000 4.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 5.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 6.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 7.0000000 8.0000000 8.0000000 8.0000000 8.0000000 8.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 9.0000000 10.0000000 10.0000000 10.0000000 10.0000000 11.000000 11.000000 11.000000 11.000000 12.000000 12.000000 13.000000 14.000000 26.000000 build map for variable # 11 NB_MapRegMean: WARNING Variance of mean targets is zero in map id 11 for key 20.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 11 for key 21.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 11 for key 22.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 11 for key 23.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 11 for key 24.000000 Unregularised mean is returned NB_MapRegMean: WARNING Variance of mean targets is zero in map id 11 for key 26.000000 Unregularised mean is returned ------------------------------ Transdef: Tab for variable 12 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 build map for variable # 12 ------------------------------ Transdef: Tab for variable 13 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 build map for variable # 13 ------------------------------ Transdef: Tab for variable 14 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 build map for variable # 14 ------------------------------ Transdef: Tab for variable 15 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0 Only one class left for trimmed mean or sigma very small -> take "normal" mean 000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 build map for variable # 15 ------------------------------ Transdef: Tab for variable 16 -112.46980 -39.830147 -35.898350 -33.940399 -32.550751 -31.435501 -30.527750 -29.720100 -28.994949 -28.333549 -27.723301 -27.156849 -26.630501 -26.130400 -25.657700 -25.195101 -24.750750 -24.323950 -23.912151 -23.514200 -23.134449 -22.759251 -22.398750 -22.040150 -21.693501 -21.345501 -21.003599 -20.667700 -20.336050 -20.005100 -19.686850 -19.369650 -19.059200 -18.750750 -18.454201 -18.149099 -17.849701 -17.547249 -17.248749 -16.944750 -16.644699 -16.340851 -16.049751 -15.757500 -15.452300 -15.158649 -14.871450 -14.571700 -14.272850 -13.976450 -13.673300 -13.377350 -13.071600 -12.765200 -12.458200 -12.149100 -11.844900 -11.535049 -11.213350 -10.905600 -10.580250 -10.256550 -9.9278507 -9.5841503 -9.2444000 -8.8998508 -8.5509005 -8.1975498 -7.8309002 -7.4580002 -7.0717502 -6.6898999 -6.3039999 -5.9007502 -5.4896002 -5.0763001 -4.6608000 -4.2245998 -3.7867999 -3.3491502 -2.9069500 -2.4723501 -2.0267999 -1.6016001 -1.1772000 -0.77749997 -0.37729999 -2.34999992E-02 0.36750001 0.92479998 1.6281500 2.5096002 3.5696499 4.8692002 6.4819002 8.5262003 11.074950 14.532650 19.843349 29.335350 129.78270 do regularised spline fit for input variable # 16 build map for variable # 16 ------------------------------ Transdef: Tab for variable 17 -73.042801 -18.728401 -14.874650 -12.911400 -11.575550 -10.530800 -9.6646996 -8.9336500 -8.2918491 -7.7326999 -7.2321501 -6.7756000 -6.3673000 -5.9922500 -5.6499500 -5.3423500 -5.0579000 -4.7995000 -4.5609999 -4.3379498 -4.1276999 -3.9347999 -3.7537999 -3.5826001 -3.4231000 -3.2679999 -3.1246500 -2.9871500 -2.8562000 -2.7335501 -2.6138999 -2.5005000 -2.3903999 -2.2830000 -2.1787000 -2.0804000 -1.9834000 -1.8890001 -1.7972500 -1.7091000 -1.6224000 -1.5393000 -1.4559500 -1.3731000 -1.2934000 -1.2165000 -1.1392000 -1.0635000 -0.98909998 -0.91630000 -0.84280002 -0.77120000 -0.70069999 -0.63104999 -0.56160003 -0.49325001 -0.42500001 -0.35720000 -0.28895000 -0.22250000 -0.15560000 -9.17000026E-02 -2.88999993E-02 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 4.67999987E-02 0.11580000 0.18979999 0.26609999 0.34380001 0.42449999 0.50870001 0.59549999 0.68580002 0.78109998 0.87889999 0.97899997 1.0865000 1.1989000 1.3168000 1.4413000 1.5775000 1.7244000 1.8833499 2.0599999 2.2535000 2.4777000 2.7267499 3.0342000 3.4099998 3.8999000 4.6008501 5.7753000 8.3580999 78.829399 do regularised spline fit for input variable # 17 build map for variable # 17 ------------------------------ Transdef: Tab for variable 18 -120.61550 -26.543550 -16.559500 -11.238100 -8.1070004 -6.0731001 -4.6255999 -3.5512500 -2.7072999 -2.0172999 -1.4335001 -0.94739997 -0.52329999 -0.15369999 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.19780000 0.49579999 0.78490001 1.0604000 1.3292501 1.5958500 1.8530999 2.1020498 2.3432000 2.5764000 2.7997999 3.0021999 3.2073500 3.3998499 3.5846000 3.7579498 3.9249501 4.0871000 4.2456999 4.3962002 4.5413499 4.6782498 4.8097501 4.9354000 5.0598998 5.1824002 5.3028998 5.4189000 5.5300999 5.6420002 5.7501998 5.8586998 5.9633002 6.0665998 6.1697001 6.2704000 6.3688998 6.4664001 6.5634499 6.6612000 6.7589998 6.8538499 6.9516001 7.0489001 7.1441002 7.2440000 7.3428998 7.4440999 7.5439000 7.6458001 7.7491999 7.8534498 7.9617000 8.0726004 8.1878500 8.3058500 8.4280996 8.5536003 8.6840000 8.8239002 8.9699497 9.1241493 9.2858000 9.4670000 9.6613503 9.8748493 10.114800 10.399200 10.721600 11.114201 11.624200 12.362700 13.459650 15.174600 17.548700 21.188301 105.46610 do regularised spline fit for input variable # 18 build map for variable # 18 ------------------------------ Transdef: Tab for variable 19 -108.54280 -25.882099 -16.314150 -11.172400 -7.7307501 -5.2227001 -3.2182002 -1.5490000 -0.27950001 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.60115004 1.3302000 1.9888999 2.5210500 2.9557500 3.3131001 3.6148000 3.8727000 4.0969501 4.2972999 4.4828000 4.6494002 4.8024001 4.9454498 5.0798998 5.2104502 5.3350000 5.4537001 5.5665002 5.6774001 5.7839999 5.8875999 5.9872999 6.0854998 6.1833000 6.2770000 6.3677001 6.4572001 6.5462499 6.6352000 6.7220001 6.8081999 6.8927002 6.9779000 7.0622001 7.1433501 7.2298999 7.3140497 7.3962998 7.4805002 7.5643001 7.6483998 7.7333999 7.8182998 7.9032998 7.9930000 8.0827999 8.1732998 8.2664003 8.3583002 8.4523001 8.5493002 8.6474495 8.7512999 8.8558502 8.9641495 9.0746002 9.1906996 9.3097000 9.4401999 9.5697002 9.7109003 9.8554001 10.011450 10.178800 10.356800 10.549900 10.766100 11.003800 11.268300 11.568100 11.923349 12.343900 12.861851 13.510000 14.328400 15.339550 16.603802 18.178900 20.260201 23.456051 73.494202 do regularised spline fit for input variable # 19 build map for variable # 19 ------------------------------ Transdef: Tab for variable 20 -101.92670 -23.095749 -14.950700 -10.248450 -6.8500500 -4.0966001 -1.8659000 -0.26805001 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.74409997 1.5451500 2.2165000 2.7448502 3.1602001 3.4971001 3.7773499 4.0210500 4.2349000 4.4305000 4.6062999 4.7655001 4.9137497 5.0540500 5.1859503 5.3132000 5.4347000 5.5493002 5.6622000 5.7708998 5.8761001 5.9783001 6.0765500 6.1763000 6.2705002 6.3629999 6.4535999 6.5440001 6.6334000 6.7209001 6.8077998 6.8927498 6.9783001 7.0632000 7.1445999 7.2319999 7.3174000 7.4001002 7.4858999 7.5699000 7.6546998 7.7407999 7.8270998 7.9137001 8.0033998 8.0948000 8.1861000 8.2789001 8.3734999 8.4675999 8.5671501 8.6672001 8.7728004 8.8781004 8.9888000 9.1002998 9.2185001 9.3413000 9.4717999 9.6056004 9.7489996 9.8962002 10.055700 10.227600 10.410300 10.610950 10.833400 11.081249 11.361200 11.681900 12.066000 12.514299 13.071400 13.776100 14.620550 15.652600 16.855301 18.201450 19.800800 21.750301 24.229650 28.027300 49.999199 do regularised spline fit for input variable # 20 build map for variable # 20 ------------------------------ Transdef: Tab for variable 21 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 0.0000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 1.00000000 build map for variable # 21 ------------------------------ Transdef: Tab for variable 22 -1.5698276 -0.63897610 -0.62506574 -0.62138510 -0.61883551 -0.60750651 -0.60750651 -0.60750651 -0.58125848 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.55358869 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.53289008 -0.46140027 -0.37355232 -0.26047993 -0.19755149 -0.19755149 -0.19324017 -0.19324017 -0.19324017 -0.15976000 -0.15976000 -0.10151577 -9.30809975E-02 -8.66560936E-02 -8.20565224E-02 -7.13868141E-02 -7.13868141E-02 -5.93438148E-02 -2.68115997E-02 -2.88772583E-03 1.47328377E-02 1.48792267E-02 9.56082344E-02 0.12159824 0.13534212 0.14300680 0.20615196 0.30152416 0.37100029 0.41030312 0.51227760 0.57777882 0.75469494 1.0924029 1.2763481 1.5115242 2.2675354 3.0176537 4.7914839 do regularised spline fit for input variable # 22 build map for variable # 22 ------------------------------ Transdef: Tab for variable 23 0.47191012 0.82865167 0.84971911 0.86454433 0.87546819 0.88282502 0.88951313 0.89632279 0.90288925 0.90823972 0.91292137 0.91643256 0.92134833 0.92415732 0.92696631 0.93164796 0.93632960 0.93820226 0.94101125 0.94484168 0.94803369 0.95037454 0.95505619 0.95505619 0.95973784 0.96129841 0.96441948 0.96709472 0.96910113 0.97191012 0.97378278 0.97752810 0.97913325 0.98314607 0.98314607 0.98665732 0.98876405 0.99117178 0.99367976 0.99563044 0.99719101 1.0007023 1.0018727 1.0056180 1.0072231 1.0112360 1.0112360 1.0147471 1.0168539 1.0192616 1.0217696 1.0237204 1.0252810 1.0287921 1.0308989 1.0337079 1.0358146 1.0393258 1.0393258 1.0440075 1.0463483 1.0486891 1.0518103 1.0533708 1.0572013 1.0603932 1.0627341 1.0674157 1.0674157 1.0720974 1.0767790 1.0786517 1.0814607 1.0861423 1.0898876 1.0955056 1.0980593 1.1011236 1.1067415 1.1111112 1.1165730 1.1204745 1.1271068 1.1329588 1.1376405 1.1460674 1.1516854 1.1610487 1.1704119 1.1797752 1.1938202 1.2078651 1.2219101 1.2421973 1.2687266 1.3014982 1.3483146 1.4138577 1.5125067 1.7078651 4.9775281 do regularised spline fit for input variable # 23 build map for variable # 23 warning: map is empty for variable 23 TOTAL CORRELATION OF ALL VARIABLES 4.4317723552579222 ROUND 1 : MAX CORR ( 4.4317720898745518 ) AFTER KILLING INPUT VARIABLE 3 CONTR 1.53370052460171042E-003 ROUND 2 : MAX CORR ( 4.4317674778003520 ) AFTER KILLING INPUT VARIABLE 22 CONTR 6.39369237283579205E-003 ROUND 3 : MAX CORR ( 4.4316703438768732 ) AFTER KILLING INPUT VARIABLE 5 CONTR 2.93417874562836543E-002 ROUND 4 : MAX CORR ( 4.4287441298235199 ) AFTER KILLING INPUT VARIABLE 10 CONTR 0.16102008990022382 ROUND 5 : MAX CORR ( 4.4249410754974763 ) AFTER KILLING INPUT VARIABLE 13 CONTR 0.18349671883041374 ROUND 6 : MAX CORR ( 4.4209679802635709 ) AFTER KILLING INPUT VARIABLE 8 CONTR 0.18747170215529577 ROUND 7 : MAX CORR ( 4.4152944571062021 ) AFTER KILLING INPUT VARIABLE 20 CONTR 0.22390341570195896 ROUND 8 : MAX CORR ( 4.4095950492255875 ) AFTER KILLING INPUT VARIABLE 19 CONTR 0.22426913474203028 ROUND 9 : MAX CORR ( 4.3978487081575617 ) AFTER KILLING INPUT VARIABLE 18 CONTR 0.32164458383700206 ROUND 10 : MAX CORR ( 4.3826882643776095 ) AFTER KILLING INPUT VARIABLE 9 CONTR 0.36485180159882918 ROUND 11 : MAX CORR ( 4.3608178423574859 ) AFTER KILLING INPUT VARIABLE 12 CONTR 0.43729185733309145 ROUND 12 : MAX CORR ( 4.3249000739579504 ) AFTER KILLING INPUT VARIABLE 15 CONTR 0.55854418312422982 ROUND 13 : MAX CORR ( 4.2793126812906355 ) AFTER KILLING INPUT VARIABLE 21 CONTR 0.62629356173174677 ROUND 14 : MAX CORR ( 4.2417233566489951 ) AFTER KILLING INPUT VARIABLE 14 CONTR 0.56595051896188842 ROUND 15 : MAX CORR ( 4.1903588944716486 ) AFTER KILLING INPUT VARIABLE 6 CONTR 0.65811045415185421 ROUND 16 : MAX CORR ( 4.1270509907289954 ) AFTER KILLING INPUT VARIABLE 7 CONTR 0.72564301443648849 ROUND 17 : MAX CORR ( 4.0173923648510179 ) AFTER KILLING INPUT VARIABLE 23 CONTR 0.94504416135645719 ROUND 18 : MAX CORR ( 3.8818607572918218 ) AFTER KILLING INPUT VARIABLE 11 CONTR 1.0346972862441548 ROUND 19 : MAX CORR ( 3.6830012424567320 ) AFTER KILLING INPUT VARIABLE 4 CONTR 1.2265173407108456 ROUND 20 : MAX CORR ( 3.2988950272733493 ) AFTER KILLING INPUT VARIABLE 16 CONTR 1.6376170953458562 ROUND 21 : MAX CORR ( 2.3434149501908634 ) AFTER KILLING INPUT VARIABLE 17 CONTR 2.3218774240236684 LAST REMAINING VARIABLE: 2 total correlation to target: 4.4317723552579222 % total significance: 38.947186017994049 sigma correlations of single variables to target: variable 2 : 2.3434149501913386 % , in sigma: 20.594338035925269 variable 3 : 0.60978741269433401 % , in sigma: 5.3589178075585853 variable 4 : 1.2906032154766249 % , in sigma: 11.342045457040179 variable 5 : 0.28211292685365252 % , in sigma: 2.4792574526564324 variable 6 : 0.85827751281528464 % , in sigma: 7.5426920128285193 variable 7 : 0.91126162434662383 % , in sigma: 8.0083255974057934 variable 8 : 0.67532385617876900 % , in sigma: 5.9348634678355099 variable 9 : 0.53793589681100362 % , in sigma: 4.7274741930275193 variable 10 : 0.13858126316626906 % , in sigma: 1.2178762360710540 variable 11 : 0.97510439986610953 % , in sigma: 8.5693870091257409 variable 12 : 0.61961922302079686 % , in sigma: 5.4453214661815474 variable 13 : 0.28768489001271946 % , in sigma: 2.5282248337052633 variable 14 : 0.21416408126548211 % , in sigma: 1.8821111832433211 variable 15 : 7.37472030868457501E-002 % , in sigma: 0.64810324328199986 variable 16 : 1.1856900115550826 % , in sigma: 10.420049979535953 variable 17 : 2.2546031086017129 % , in sigma: 19.813844130165869 variable 18 : 0.85557825617305105 % , in sigma: 7.5189704761321110 variable 19 : 0.47956128817750560 % , in sigma: 4.2144679826613425 variable 20 : 0.55200331272958048 % , in sigma: 4.8511010900461082 variable 21 : 0.69836407301128789 % , in sigma: 6.1373448994023638 variable 22 : 1.0734026137222656 % , in sigma: 9.4332488037754931 variable 23 : 1.1338635012744145 % , in sigma: 9.9645895960237265 variables sorted by significance: 1 most relevant variable 2 corr 2.3434150 , in sigma: 20.594338666081480 2 most relevant variable 17 corr 2.3218775 , in sigma: 20.405062999199927 3 most relevant variable 16 corr 1.6376171 , in sigma: 14.391663908621574 4 most relevant variable 4 corr 1.2265173 , in sigma: 10.778847462046485 5 most relevant variable 11 corr 1.0346973 , in sigma: 9.0930997263620270 6 most relevant variable 23 corr 0.94504416 , in sigma: 8.3052123935825026 7 most relevant variable 7 corr 0.72564304 , in sigma: 6.3770771933528252 8 most relevant variable 6 corr 0.65811044 , in sigma: 5.7835889715733266 9 most relevant variable 14 corr 0.56595051 , in sigma: 4.9736715100451514 10 most relevant variable 21 corr 0.62629354 , in sigma: 5.5039765242779621 11 most relevant variable 15 corr 0.55854416 , in sigma: 4.9085831837724765 12 most relevant variable 12 corr 0.43729186 , in sigma: 3.8429969034792832 13 most relevant variable 9 corr 0.36485180 , in sigma: 3.2063810785581666 14 most relevant variable 18 corr 0.32164457 , in sigma: 2.8266684447632957 15 most relevant variable 19 corr 0.22426914 , in sigma: 1.9709161681453065 16 most relevant variable 20 corr 0.22390342 , in sigma: 1.9677021642346724 17 most relevant variable 8 corr 0.18747170 , in sigma: 1.6475339193145750 18 most relevant variable 13 corr 0.18349671 , in sigma: 1.6126010243470077 19 most relevant variable 10 corr 0.16102009 , in sigma: 1.4150725057174158 20 most relevant variable 5 corr 2.93417871E-02 , in sigma: 0.25786072674106719 21 most relevant variable 22 corr 6.39369246E-03 , in sigma: 5.61888809874174985E-002 22 most relevant variable 3 corr 1.53370050E-03 , in sigma: 1.34784266829538254E-002 global correlations between input variables: variable 2 : 36.419503618861661 % variable 3 : 84.753131297619191 % variable 4 : 44.658324684979100 % variable 5 : 59.317991411940305 % variable 6 : 25.638807452274904 % variable 7 : 33.229563429598123 % variable 8 : 64.500996321690039 % variable 9 : 18.692482236166313 % variable 10 : 43.186312732154548 % variable 11 : 35.795473085133231 % variable 12 : 90.398715552954741 % variable 13 : 89.092426399911957 % variable 14 : 94.083329832200434 % variable 15 : 79.681557545189435 % variable 16 : 48.964204200849707 % variable 17 : 36.640515227897140 % variable 18 : 67.847199408053143 % variable 19 : 92.843778674684529 % variable 20 : 92.543045546237920 % variable 21 : 64.613873710546699 % variable 22 : 71.990790506839630 % variable 23 : 21.380658430727781 % significance loss when removing single variables: variable 2 : corr = 2.2243310744938660 % , sigma = 19.547808230974752 variable 3 : corr = 1.53370052427822439E-003 % , sigma = 1.34784268745416248E-002 variable 4 : corr = 1.2658704988970224 % , sigma = 11.124690043418072 variable 5 : corr = 2.91951758297426534E-002 % , sigma = 0.25657228140790983 variable 6 : corr = 0.67376054476487046 % , sigma = 5.9211248153144878 variable 7 : corr = 0.71592467413595751 % , sigma = 6.2916705153782999 variable 8 : corr = 0.17248736216962673 % , sigma = 1.5158489294251198 variable 9 : corr = 0.37908584333552581 % , sigma = 3.3314723035492229 variable 10 : corr = 0.15112851539109343 % , sigma = 1.3281436702354346 variable 11 : corr = 0.86259803958018000 % , sigma = 7.5806615532559416 variable 12 : corr = 0.29644990086025813 % , sigma = 2.6052532730211539 variable 13 : corr = 0.17937402129327104 % , sigma = 1.5763700871991364 variable 14 : corr = 0.68147574968542668 % , sigma = 5.9889273776124696 variable 15 : corr = 0.45406138916407374 % , sigma = 3.9903704364193961 variable 16 : corr = 1.2938085398503476 % , sigma = 11.370214404951794 variable 17 : corr = 2.5902346673826200 % , sigma = 22.763432625576872 variable 18 : corr = 0.32586782869034353 % , sigma = 2.8637831377383538 variable 19 : corr = 0.29963806185337144 % , sigma = 2.6332713861597448 variable 20 : corr = 0.24467170504644317 % , sigma = 2.1502174854441520 variable 21 : corr = 0.44416114569876969 % , sigma = 3.9033653754737085 variable 22 : corr = 5.65910133055731908E-003 % , sigma = 4.97331664507542764E-002 variable 23 : corr = 0.92989541524898867 % , sigma = 8.1720825917454913 Keep only 13 most significant input variables Sum of Weights for output node 2 772320.00000000000 FLAT2DEF: TAB(KK=1, II= 2 ) = -5.2587881 NVar: 14.000000 2771 --------- Entering internal boost mode: --------- Starting analysis with 30 variables. PREPRO: (sigma of derived input)/eigenvalue # 1 : 2.9717510 PREPRO: (sigma of derived input)/eigenvalue # 2 : 1.7242168 PREPRO: (sigma of derived input)/eigenvalue # 3 : 1.6336902 PREPRO: (sigma of derived input)/eigenvalue # 4 : 1.5285585 PREPRO: (sigma of derived input)/eigenvalue # 5 : 1.5178161 PREPRO: (sigma of derived input)/eigenvalue # 6 : 1.2955300 PREPRO: (sigma of derived input)/eigenvalue # 7 : 1.2020148 PREPRO: (sigma of derived input)/eigenvalue # 8 : 1.0646738 PREPRO: (sigma of derived input)/eigenvalue # 9 : 1.0354021 PREPRO: (sigma of derived input)/eigenvalue # 10 : 0.99882489 PREPRO: (sigma of derived input)/eigenvalue # 11 : 0.94528913 PREPRO: (sigma of derived input)/eigenvalue # 12 : 0.88873327 PREPRO: (sigma of derived input)/eigenvalue # 13 : 0.78335899 PREPRO: (sigma of derived input)/eigenvalue # 14 : 0.69954455 PREPRO: (sigma of derived input)/eigenvalue # 15 : 0.60476846 PREPRO: (sigma of derived input)/eigenvalue # 16 : 0.57779759 PREPRO: (sigma of derived input)/eigenvalue # 17 : 0.51985401 PREPRO: (sigma of derived input)/eigenvalue # 18 : 0.46715418 PREPRO: (sigma of derived input)/eigenvalue # 19 : 0.42465192 PREPRO: (sigma of derived input)/eigenvalue # 20 : 0.37348381 PREPRO: (sigma of derived input)/eigenvalue # 21 : 0.34393167 PREPRO: (sigma of derived input)/eigenvalue # 22 : 0.30220103 PREPRO: (sigma of derived input)/eigenvalue # 23 : 0.20275390 PREPRO: (sigma of derived input)/eigenvalue # 24 : 0.12265674 PREPRO: (sigma of derived input)/eigenvalue # 25 : 3.08008050E-04 PREPRO: (sigma of derived input)/eigenvalue # 26 : 1.56717753E-04 PREPRO: (sigma of derived input)/eigenvalue # 27 : 2.65336766E-08 PREPRO: (sigma of derived input)/eigenvalue # 28 : 1.27290406E-07 PREPRO: (sigma of derived input)/eigenvalue # 29 : 1.88592530E-04 PREPRO: (sigma of derived input)/eigenvalue # 30 : 4.50634834E-04 Using 24 variables out of 30 for boost net! VARIABLES BEFORE BOOST 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 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 0 0.1 3.0 1.7 1.6 1.5 1.5 1.3 1.2 1.1 1.0 1.0 0.9 0.9 0.8 0.7 0.6 0.6 0.5 0.5 0.4 0.4 0.3 0.3 0.2 0.1 1 100.0 -0.4 0.7 0.6 1.0 -1.7 -0.1 2.8 0.8 0.8 -0.0 0.2 1.0 0.1 -0.2 0.2 0.3 -0.1 -0.6 0.1 -0.1 -0.2 -0.1 -0.1 0.5 2 -0.4 100.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 0.0 0.0 -0.0 0.0 -0.0 0.0 -0.0 0.0 -0.0 0.0 -0.0 -0.0 3 0.7 -0.0 100.0 -0.0 0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 0.0 0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 0.0 0.0 0.0 4 0.6 0.0 -0.0 100.0 0.0 -0.0 -0.0 -0.0 0.0 -0.0 0.0 -0.0 0.0 0.0 0.0 0.0 0.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 0.0 5 1.0 -0.0 0.0 0.0 100.0 -0.0 -0.0 -0.0 0.0 -0.0 0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0 -0.0 0.0 0.0 0.0 0.0 0.0 0.0 6 -1.7 -0.0 0.0 -0.0 -0.0 100.0 -0.0 0.0 -0.0 0.0 -0.0 0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 0.0 7 -0.1 0.0 0.0 -0.0 -0.0 -0.0 100.0 0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 -0.0 8 2.8 0.0 -0.0 -0.0 -0.0 0.0 0.0 100.0 -0.0 -0.0 -0.0 -0.0 0.0 -0.0 0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 -0.0 -0.0 -0.0 -0.0 9 0.8 0.0 0.0 0.0 0.0 -0.0 0.0 -0.0 100.0 -0.0 0.0 -0.0 0.0 -0.0 -0.0 0.0 -0.0 -0.0 -0.0 -0.0 0.0 -0.0 0.0 0.0 -0.0 10 0.8 -0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 -0.0 100.0 0.0 0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0 0.0 0.0 0.0 -0.0 0.0 11 -0.0 -0.0 -0.0 0.0 0.0 -0.0 -0.0 -0.0 0.0 0.0 100.0 -0.0 0.0 -0.0 0.0 0.0 0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 0.0 -0.0 12 0.2 0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 100.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 0.0 0.0 -0.0 0.0 -0.0 -0.0 -0.0 13 1.0 -0.0 0.0 0.0 -0.0 0.0 0.0 0.0 0.0 -0.0 0.0 -0.0 100.0 0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 0.0 0.0 -0.0 0.0 14 0.1 0.0 -0.0 0.0 -0.0 0.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0 0.0 100.0 0.0 -0.0 -0.0 -0.0 0.0 0.0 0.0 -0.0 0.0 0.0 0.0 15 -0.2 0.0 0.0 0.0 -0.0 -0.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 0.0 100.0 0.0 -0.0 0.0 -0.0 0.0 0.0 0.0 0.0 -0.0 -0.0 16 0.2 -0.0 0.0 0.0 -0.0 -0.0 0.0 0.0 0.0 -0.0 0.0 -0.0 0.0 -0.0 0.0 100.0 -0.0 -0.0 0.0 0.0 0.0 -0.0 -0.0 -0.0 -0.0 17 0.3 0.0 0.0 0.0 -0.0 0.0 -0.0 0.0 -0.0 -0.0 0.0 -0.0 0.0 -0.0 -0.0 -0.0 100.0 -0.0 0.0 0.0 0.0 0.0 0.0 -0.0 0.0 18 -0.1 -0.0 0.0 -0.0 0.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 -0.0 100.0 -0.0 0.0 -0.0 0.0 0.0 -0.0 0.0 19 -0.6 0.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 0.0 -0.0 0.0 0.0 -0.0 100.0 0.0 0.0 0.0 -0.0 -0.0 0.0 20 0.1 -0.0 0.0 -0.0 0.0 0.0 0.0 0.0 -0.0 0.0 -0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 100.0 0.0 -0.0 0.0 0.0 -0.0 21 -0.1 0.0 0.0 -0.0 0.0 -0.0 -0.0 -0.0 0.0 0.0 -0.0 -0.0 -0.0 0.0 0.0 0.0 0.0 -0.0 0.0 0.0 100.0 0.0 -0.0 -0.0 -0.0 22 -0.2 -0.0 -0.0 0.0 0.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 0.0 0.0 -0.0 0.0 -0.0 0.0 0.0 0.0 -0.0 0.0 100.0 0.0 0.0 -0.0 23 -0.1 0.0 0.0 0.0 0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 0.0 0.0 -0.0 0.0 0.0 -0.0 0.0 -0.0 0.0 100.0 0.0 0.0 24 -0.1 -0.0 0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 -0.0 0.0 -0.0 -0.0 0.0 -0.0 -0.0 -0.0 -0.0 -0.0 0.0 -0.0 0.0 0.0 100.0 -0.0 25 0.5 -0.0 0.0 0.0 0.0 0.0 -0.0 -0.0 -0.0 0.0 -0.0 -0.0 0.0 0.0 -0.0 -0.0 0.0 0.0 0.0 -0.0 -0.0 -0.0 0.0 -0.0 100.0 TOTAL CORRELATION TO TARGET (diagonal) 3.9870939238214707 ------------------------------------- Teacher: actual network topology: Nodes(1) = 25 Nodes(2) = 26 Nodes(3) = 1 ------------------------------------- NBPRESET: start with small weights from bias node for IFIXSHAPE > 0 trainings --------------------------------------------------- Iteration : 1 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 156.61919 sigma out 26 active outputs RANK 2 NODE 2 --> 57.396912 sigma out 26 active outputs RANK 3 NODE 8 --> 50.136742 sigma out 26 active outputs RANK 4 NODE 5 --> 47.548370 sigma out 26 active outputs RANK 5 NODE 9 --> 41.849773 sigma out 26 active outputs RANK 6 NODE 16 --> 41.461475 sigma out 26 active outputs RANK 7 NODE 22 --> 40.616734 sigma out 26 active outputs RANK 8 NODE 18 --> 40.506977 sigma out 26 active outputs RANK 9 NODE 7 --> 39.245293 sigma out 26 active outputs RANK 10 NODE 13 --> 37.458797 sigma out 26 active outputs RANK 11 NODE 4 --> 37.193027 sigma out 26 active outputs RANK 12 NODE 23 --> 36.959171 sigma out 26 active outputs RANK 13 NODE 3 --> 36.713806 sigma out 26 active outputs RANK 14 NODE 17 --> 35.918980 sigma out 26 active outputs RANK 15 NODE 25 --> 35.712948 sigma out 26 active outputs RANK 16 NODE 6 --> 35.149933 sigma out 26 active outputs RANK 17 NODE 21 --> 34.639477 sigma out 26 active outputs RANK 18 NODE 10 --> 34.282616 sigma out 26 active outputs RANK 19 NODE 19 --> 33.420151 sigma out 26 active outputs RANK 20 NODE 11 --> 32.068554 sigma out 26 active outputs RANK 21 NODE 15 --> 31.859797 sigma out 26 active outputs RANK 22 NODE 20 --> 30.616590 sigma out 26 active outputs RANK 23 NODE 24 --> 29.188143 sigma out 26 active outputs RANK 24 NODE 12 --> 28.095165 sigma out 26 active outputs RANK 25 NODE 14 --> 23.487123 sigma out 26 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 19 --> 107.73460 sigma in 25 act. ( 197.16626 sig out 1 act.) RANK 2 NODE 8 --> 95.659912 sigma in 25 act. ( 171.92336 sig out 1 act.) RANK 3 NODE 24 --> 59.794601 sigma in 25 act. ( 121.85973 sig out 1 act.) RANK 4 NODE 13 --> 56.137897 sigma in 25 act. ( 118.74433 sig out 1 act.) RANK 5 NODE 21 --> 50.506489 sigma in 25 act. ( 95.874268 sig out 1 act.) RANK 6 NODE 22 --> 48.669647 sigma in 25 act. ( 60.660347 sig out 1 act.) RANK 7 NODE 7 --> 45.776699 sigma in 25 act. ( 70.126373 sig out 1 act.) RANK 8 NODE 15 --> 45.529488 sigma in 25 act. ( 67.497566 sig out 1 act.) RANK 9 NODE 20 --> 42.900623 sigma in 25 act. ( 85.497360 sig out 1 act.) RANK 10 NODE 9 --> 41.738338 sigma in 25 act. ( 61.423599 sig out 1 act.) RANK 11 NODE 25 --> 40.999844 sigma in 25 act. ( 41.586117 sig out 1 act.) RANK 12 NODE 17 --> 40.664696 sigma in 25 act. ( 40.851292 sig out 1 act.) RANK 13 NODE 23 --> 39.268822 sigma in 25 act. ( 99.412720 sig out 1 act.) RANK 14 NODE 5 --> 37.224758 sigma in 25 act. ( 37.677967 sig out 1 act.) RANK 15 NODE 18 --> 36.054348 sigma in 25 act. ( 38.563072 sig out 1 act.) RANK 16 NODE 11 --> 35.640709 sigma in 25 act. ( 13.072208 sig out 1 act.) RANK 17 NODE 10 --> 33.899651 sigma in 25 act. ( 35.819073 sig out 1 act.) RANK 18 NODE 4 --> 33.879688 sigma in 25 act. ( 19.334198 sig out 1 act.) RANK 19 NODE 6 --> 33.645271 sigma in 25 act. ( 55.268803 sig out 1 act.) RANK 20 NODE 26 --> 32.420082 sigma in 25 act. ( 46.631535 sig out 1 act.) RANK 21 NODE 12 --> 32.355091 sigma in 25 act. ( 31.085369 sig out 1 act.) RANK 22 NODE 16 --> 32.247688 sigma in 25 act. ( 18.183590 sig out 1 act.) RANK 23 NODE 14 --> 30.229614 sigma in 25 act. ( 15.888254 sig out 1 act.) RANK 24 NODE 3 --> 29.630915 sigma in 25 act. ( 12.960270 sig out 1 act.) RANK 25 NODE 2 --> 28.198730 sigma in 25 act. ( 7.8232646 sig out 1 act.) RANK 26 NODE 1 --> 26.937309 sigma in 25 act. ( 18.988983 sig out 1 act.) sorted by output significance RANK 1 NODE 19 --> 197.16626 sigma out 1 act.( 107.73460 sig in 25 act.) RANK 2 NODE 8 --> 171.92336 sigma out 1 act.( 95.659912 sig in 25 act.) RANK 3 NODE 24 --> 121.85973 sigma out 1 act.( 59.794601 sig in 25 act.) RANK 4 NODE 13 --> 118.74433 sigma out 1 act.( 56.137897 sig in 25 act.) RANK 5 NODE 23 --> 99.412720 sigma out 1 act.( 39.268822 sig in 25 act.) RANK 6 NODE 21 --> 95.874268 sigma out 1 act.( 50.506489 sig in 25 act.) RANK 7 NODE 20 --> 85.497360 sigma out 1 act.( 42.900623 sig in 25 act.) RANK 8 NODE 7 --> 70.126373 sigma out 1 act.( 45.776699 sig in 25 act.) RANK 9 NODE 15 --> 67.497566 sigma out 1 act.( 45.529488 sig in 25 act.) RANK 10 NODE 9 --> 61.423599 sigma out 1 act.( 41.738338 sig in 25 act.) RANK 11 NODE 22 --> 60.660347 sigma out 1 act.( 48.669647 sig in 25 act.) RANK 12 NODE 6 --> 55.268803 sigma out 1 act.( 33.645271 sig in 25 act.) RANK 13 NODE 26 --> 46.631535 sigma out 1 act.( 32.420082 sig in 25 act.) RANK 14 NODE 25 --> 41.586117 sigma out 1 act.( 40.999844 sig in 25 act.) RANK 15 NODE 17 --> 40.851292 sigma out 1 act.( 40.664696 sig in 25 act.) RANK 16 NODE 18 --> 38.563072 sigma out 1 act.( 36.054348 sig in 25 act.) RANK 17 NODE 5 --> 37.677967 sigma out 1 act.( 37.224758 sig in 25 act.) RANK 18 NODE 10 --> 35.819073 sigma out 1 act.( 33.899651 sig in 25 act.) RANK 19 NODE 12 --> 31.085369 sigma out 1 act.( 32.355091 sig in 25 act.) RANK 20 NODE 4 --> 19.334198 sigma out 1 act.( 33.879688 sig in 25 act.) RANK 21 NODE 1 --> 18.988983 sigma out 1 act.( 26.937309 sig in 25 act.) RANK 22 NODE 16 --> 18.183590 sigma out 1 act.( 32.247688 sig in 25 act.) RANK 23 NODE 14 --> 15.888254 sigma out 1 act.( 30.229614 sig in 25 act.) RANK 24 NODE 11 --> 13.072208 sigma out 1 act.( 35.640709 sig in 25 act.) RANK 25 NODE 3 --> 12.960270 sigma out 1 act.( 29.630915 sig in 25 act.) RANK 26 NODE 2 --> 7.8232646 sigma out 1 act.( 28.198730 sig in 25 act.) RANK 1 NODE 1 --> 395.21368 sigma in 26 active inputs SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 89.049080 sigma out 26 active outputs RANK 2 NODE 2 --> 26.013767 sigma out 26 active outputs RANK 3 NODE 8 --> 19.929619 sigma out 26 active outputs RANK 4 NODE 5 --> 19.829891 sigma out 26 active outputs RANK 5 NODE 7 --> 16.583935 sigma out 26 active outputs RANK 6 NODE 3 --> 15.569375 sigma out 26 active outputs RANK 7 NODE 6 --> 15.442654 sigma out 26 active outputs RANK 8 NODE 4 --> 15.107931 sigma out 26 active outputs RANK 9 NODE 9 --> 14.344986 sigma out 26 active outputs RANK 10 NODE 13 --> 12.157649 sigma out 26 active outputs RANK 11 NODE 17 --> 10.561537 sigma out 26 active outputs RANK 12 NODE 10 --> 9.9669809 sigma out 26 active outputs RANK 13 NODE 12 --> 9.7108192 sigma out 26 active outputs RANK 14 NODE 14 --> 8.4282837 sigma out 26 active outputs RANK 15 NODE 16 --> 8.1743422 sigma out 26 active outputs RANK 16 NODE 18 --> 7.9136868 sigma out 26 active outputs RANK 17 NODE 15 --> 7.8942161 sigma out 26 active outputs RANK 18 NODE 22 --> 7.4194088 sigma out 26 active outputs RANK 19 NODE 19 --> 6.5601039 sigma out 26 active outputs RANK 20 NODE 21 --> 5.9979386 sigma out 26 active outputs RANK 21 NODE 11 --> 5.8009133 sigma out 26 active outputs RANK 22 NODE 20 --> 5.5829444 sigma out 26 active outputs RANK 23 NODE 23 --> 4.3783689 sigma out 26 active outputs RANK 24 NODE 24 --> 2.4876328 sigma out 26 active outputs RANK 25 NODE 25 --> 1.9904391 sigma out 26 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 19 --> 58.566055 sigma in 25 act. ( 71.992157 sig out 1 act.) RANK 2 NODE 8 --> 47.073582 sigma in 25 act. ( 67.630356 sig out 1 act.) RANK 3 NODE 24 --> 30.544203 sigma in 25 act. ( 29.322712 sig out 1 act.) RANK 4 NODE 13 --> 30.347239 sigma in 25 act. ( 36.944973 sig out 1 act.) RANK 5 NODE 21 --> 25.990995 sigma in 25 act. ( 26.519697 sig out 1 act.) RANK 6 NODE 20 --> 22.777693 sigma in 25 act. ( 19.032518 sig out 1 act.) RANK 7 NODE 23 --> 21.669127 sigma in 25 act. ( 22.384813 sig out 1 act.) RANK 8 NODE 7 --> 18.745731 sigma in 25 act. ( 16.612814 sig out 1 act.) RANK 9 NODE 6 --> 15.501609 sigma in 25 act. ( 14.039507 sig out 1 act.) RANK 10 NODE 9 --> 15.160383 sigma in 25 act. ( 14.478486 sig out 1 act.) RANK 11 NODE 15 --> 14.991586 sigma in 25 act. ( 18.579575 sig out 1 act.) RANK 12 NODE 22 --> 14.788045 sigma in 25 act. ( 15.769503 sig out 1 act.) RANK 13 NODE 26 --> 12.493440 sigma in 25 act. ( 12.335743 sig out 1 act.) RANK 14 NODE 17 --> 11.322448 sigma in 25 act. ( 10.131786 sig out 1 act.) RANK 15 NODE 25 --> 11.183815 sigma in 25 act. ( 9.5780401 sig out 1 act.) RANK 16 NODE 5 --> 10.501110 sigma in 25 act. ( 8.5677633 sig out 1 act.) RANK 17 NODE 18 --> 10.204205 sigma in 25 act. ( 9.6740541 sig out 1 act.) RANK 18 NODE 10 --> 9.8884153 sigma in 25 act. ( 7.8174891 sig out 1 act.) RANK 19 NODE 12 --> 8.6089306 sigma in 25 act. ( 7.8847885 sig out 1 act.) RANK 20 NODE 11 --> 7.7307777 sigma in 25 act. ( 3.1814966 sig out 1 act.) RANK 21 NODE 4 --> 7.1375751 sigma in 25 act. ( 4.7469306 sig out 1 act.) RANK 22 NODE 16 --> 6.4945173 sigma in 25 act. ( 4.5532169 sig out 1 act.) RANK 23 NODE 14 --> 6.4510036 sigma in 25 act. ( 3.6414583 sig out 1 act.) RANK 24 NODE 3 --> 6.3557372 sigma in 25 act. ( 3.1009326 sig out 1 act.) RANK 25 NODE 1 --> 6.0219073 sigma in 25 act. ( 5.1574216 sig out 1 act.) RANK 26 NODE 2 --> 5.9407878 sigma in 25 act. ( 1.7856086 sig out 1 act.) sorted by output significance RANK 1 NODE 19 --> 71.992157 sigma out 1 act.( 58.566055 sig in 25 act.) RANK 2 NODE 8 --> 67.630356 sigma out 1 act.( 47.073582 sig in 25 act.) RANK 3 NODE 13 --> 36.944973 sigma out 1 act.( 30.347239 sig in 25 act.) RANK 4 NODE 24 --> 29.322712 sigma out 1 act.( 30.544203 sig in 25 act.) RANK 5 NODE 21 --> 26.519697 sigma out 1 act.( 25.990995 sig in 25 act.) RANK 6 NODE 23 --> 22.384813 sigma out 1 act.( 21.669127 sig in 25 act.) RANK 7 NODE 20 --> 19.032518 sigma out 1 act.( 22.777693 sig in 25 act.) RANK 8 NODE 15 --> 18.579575 sigma out 1 act.( 14.991586 sig in 25 act.) RANK 9 NODE 7 --> 16.612814 sigma out 1 act.( 18.745731 sig in 25 act.) RANK 10 NODE 22 --> 15.769503 sigma out 1 act.( 14.788045 sig in 25 act.) RANK 11 NODE 9 --> 14.478486 sigma out 1 act.( 15.160383 sig in 25 act.) RANK 12 NODE 6 --> 14.039507 sigma out 1 act.( 15.501609 sig in 25 act.) RANK 13 NODE 26 --> 12.335743 sigma out 1 act.( 12.493440 sig in 25 act.) RANK 14 NODE 17 --> 10.131786 sigma out 1 act.( 11.322448 sig in 25 act.) RANK 15 NODE 18 --> 9.6740541 sigma out 1 act.( 10.204205 sig in 25 act.) RANK 16 NODE 25 --> 9.5780401 sigma out 1 act.( 11.183815 sig in 25 act.) RANK 17 NODE 5 --> 8.5677633 sigma out 1 act.( 10.501110 sig in 25 act.) RANK 18 NODE 12 --> 7.8847885 sigma out 1 act.( 8.6089306 sig in 25 act.) RANK 19 NODE 10 --> 7.8174891 sigma out 1 act.( 9.8884153 sig in 25 act.) RANK 20 NODE 1 --> 5.1574216 sigma out 1 act.( 6.0219073 sig in 25 act.) RANK 21 NODE 4 --> 4.7469306 sigma out 1 act.( 7.1375751 sig in 25 act.) RANK 22 NODE 16 --> 4.5532169 sigma out 1 act.( 6.4945173 sig in 25 act.) RANK 23 NODE 14 --> 3.6414583 sigma out 1 act.( 6.4510036 sig in 25 act.) RANK 24 NODE 11 --> 3.1814966 sigma out 1 act.( 7.7307777 sig in 25 act.) RANK 25 NODE 3 --> 3.1009326 sigma out 1 act.( 6.3557372 sig in 25 act.) RANK 26 NODE 2 --> 1.7856086 sigma out 1 act.( 5.9407878 sig in 25 act.) RANK 1 NODE 1 --> 124.77013 sigma in 26 active inputs *********************************************** *** Learn Path 1 *** loss function: -0.58399951 *** contribution from regularisation: 5.30896825E-04 *** contribution from error: -0.58453041 *** contribution from DIAG: 2.96208395E-06 *********************************************** --------------------------------------------------- Iteration : 2 *********************************************** *** Learn Path 2 *** loss function: -0.67094201 *** contribution from regularisation: 1.02933217E-03 *** contribution from error: -0.67197132 *** contribution from DIAG: 7.97460928E-07 *********************************************** --------------------------------------------------- Iteration : 3 *********************************************** *** Learn Path 3 *** loss function: -0.67236280 *** contribution from regularisation: 6.76298980E-04 *** contribution from error: -0.67303908 *** contribution from DIAG: 7.45221598E-07 *********************************************** --------------------------------------------------- Iteration : 4 *********************************************** *** Learn Path 4 *** loss function: -0.66724968 *** contribution from regularisation: 7.69657257E-04 *** contribution from error: -0.66801935 *** contribution from DIAG: 1.75041409E-04 *********************************************** --------------------------------------------------- Iteration : 5 *********************************************** *** Learn Path 5 *** loss function: -0.67210281 *** contribution from regularisation: 8.91695032E-04 *** contribution from error: -0.67299449 *** contribution from DIAG: 4.27216537E-06 *********************************************** --------------------------------------------------- Iteration : 6 *********************************************** *** Learn Path 6 *** loss function: -0.67221475 *** contribution from regularisation: 9.03197040E-04 *** contribution from error: -0.67311794 *** contribution from DIAG: 2.54387919E-06 *********************************************** --------------------------------------------------- Iteration : 7 *********************************************** *** Learn Path 7 *** loss function: -0.67214042 *** contribution from regularisation: 9.14200442E-04 *** contribution from error: -0.67305464 *** contribution from DIAG: 2.11928977E-06 *********************************************** --------------------------------------------------- Iteration : 8 *********************************************** *** Learn Path 8 *** loss function: -0.67212981 *** contribution from regularisation: 9.09697963E-04 *** contribution from error: -0.67303950 *** contribution from DIAG: 2.08290135E-06 *********************************************** --------------------------------------------------- Iteration : 9 *********************************************** *** Learn Path 9 *** loss function: -0.67212838 *** contribution from regularisation: 9.10783361E-04 *** contribution from error: -0.67303914 *** contribution from DIAG: 2.05778224E-06 *********************************************** --------------------------------------------------- Iteration : 10 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 96.122864 sigma out 26 active outputs RANK 2 NODE 2 --> 26.955957 sigma out 26 active outputs RANK 3 NODE 8 --> 22.187050 sigma out 26 active outputs RANK 4 NODE 5 --> 20.982700 sigma out 26 active outputs RANK 5 NODE 6 --> 17.443157 sigma out 26 active outputs RANK 6 NODE 7 --> 17.431334 sigma out 26 active outputs RANK 7 NODE 3 --> 16.986254 sigma out 26 active outputs RANK 8 NODE 4 --> 16.277948 sigma out 26 active outputs RANK 9 NODE 9 --> 15.745130 sigma out 26 active outputs RANK 10 NODE 13 --> 13.465328 sigma out 26 active outputs RANK 11 NODE 10 --> 11.332355 sigma out 26 active outputs RANK 12 NODE 17 --> 11.172565 sigma out 26 active outputs RANK 13 NODE 12 --> 10.785685 sigma out 26 active outputs RANK 14 NODE 18 --> 10.169722 sigma out 26 active outputs RANK 15 NODE 16 --> 9.9945326 sigma out 26 active outputs RANK 16 NODE 15 --> 9.4656906 sigma out 26 active outputs RANK 17 NODE 14 --> 9.1973820 sigma out 26 active outputs RANK 18 NODE 22 --> 8.8984442 sigma out 26 active outputs RANK 19 NODE 19 --> 8.7700796 sigma out 26 active outputs RANK 20 NODE 21 --> 7.7774673 sigma out 26 active outputs RANK 21 NODE 11 --> 7.6684880 sigma out 26 active outputs RANK 22 NODE 20 --> 7.4499078 sigma out 26 active outputs RANK 23 NODE 23 --> 6.4445343 sigma out 26 active outputs RANK 24 NODE 24 --> 4.5298848 sigma out 26 active outputs RANK 25 NODE 25 --> 4.0688434 sigma out 26 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 19 --> 59.604416 sigma in 25 act. ( 74.046288 sig out 1 act.) RANK 2 NODE 8 --> 47.946793 sigma in 25 act. ( 69.363152 sig out 1 act.) RANK 3 NODE 24 --> 33.241062 sigma in 25 act. ( 30.690298 sig out 1 act.) RANK 4 NODE 13 --> 32.096508 sigma in 25 act. ( 39.009247 sig out 1 act.) RANK 5 NODE 21 --> 28.536543 sigma in 25 act. ( 28.939102 sig out 1 act.) RANK 6 NODE 20 --> 27.199089 sigma in 25 act. ( 21.370701 sig out 1 act.) RANK 7 NODE 23 --> 23.996431 sigma in 25 act. ( 24.500315 sig out 1 act.) RANK 8 NODE 7 --> 22.531174 sigma in 25 act. ( 18.651714 sig out 1 act.) RANK 9 NODE 6 --> 18.372660 sigma in 25 act. ( 16.717299 sig out 1 act.) RANK 10 NODE 9 --> 17.437635 sigma in 25 act. ( 16.016260 sig out 1 act.) RANK 11 NODE 22 --> 16.405090 sigma in 25 act. ( 15.717970 sig out 1 act.) RANK 12 NODE 15 --> 16.281195 sigma in 25 act. ( 18.484596 sig out 1 act.) RANK 13 NODE 26 --> 15.117629 sigma in 25 act. ( 14.711432 sig out 1 act.) RANK 14 NODE 17 --> 14.320770 sigma in 25 act. ( 11.978915 sig out 1 act.) RANK 15 NODE 5 --> 13.612177 sigma in 25 act. ( 10.030907 sig out 1 act.) RANK 16 NODE 10 --> 13.246193 sigma in 25 act. ( 9.9335079 sig out 1 act.) RANK 17 NODE 18 --> 12.905733 sigma in 25 act. ( 10.806815 sig out 1 act.) RANK 18 NODE 25 --> 12.778802 sigma in 25 act. ( 9.7138214 sig out 1 act.) RANK 19 NODE 12 --> 11.047687 sigma in 25 act. ( 9.4851799 sig out 1 act.) RANK 20 NODE 11 --> 10.283065 sigma in 25 act. ( 5.0188622 sig out 1 act.) RANK 21 NODE 16 --> 9.9734564 sigma in 25 act. ( 7.6304274 sig out 1 act.) RANK 22 NODE 4 --> 9.5003529 sigma in 25 act. ( 6.0752950 sig out 1 act.) RANK 23 NODE 14 --> 9.1558723 sigma in 25 act. ( 5.3386607 sig out 1 act.) RANK 24 NODE 1 --> 8.9254675 sigma in 25 act. ( 7.7275672 sig out 1 act.) RANK 25 NODE 3 --> 8.6352177 sigma in 25 act. ( 4.8866148 sig out 1 act.) RANK 26 NODE 2 --> 8.1367912 sigma in 25 act. ( 3.4494467 sig out 1 act.) sorted by output significance RANK 1 NODE 19 --> 74.046288 sigma out 1 act.( 59.604416 sig in 25 act.) RANK 2 NODE 8 --> 69.363152 sigma out 1 act.( 47.946793 sig in 25 act.) RANK 3 NODE 13 --> 39.009247 sigma out 1 act.( 32.096508 sig in 25 act.) RANK 4 NODE 24 --> 30.690298 sigma out 1 act.( 33.241062 sig in 25 act.) RANK 5 NODE 21 --> 28.939102 sigma out 1 act.( 28.536543 sig in 25 act.) RANK 6 NODE 23 --> 24.500315 sigma out 1 act.( 23.996431 sig in 25 act.) RANK 7 NODE 20 --> 21.370701 sigma out 1 act.( 27.199089 sig in 25 act.) RANK 8 NODE 7 --> 18.651714 sigma out 1 act.( 22.531174 sig in 25 act.) RANK 9 NODE 15 --> 18.484596 sigma out 1 act.( 16.281195 sig in 25 act.) RANK 10 NODE 6 --> 16.717299 sigma out 1 act.( 18.372660 sig in 25 act.) RANK 11 NODE 9 --> 16.016260 sigma out 1 act.( 17.437635 sig in 25 act.) RANK 12 NODE 22 --> 15.717970 sigma out 1 act.( 16.405090 sig in 25 act.) RANK 13 NODE 26 --> 14.711432 sigma out 1 act.( 15.117629 sig in 25 act.) RANK 14 NODE 17 --> 11.978915 sigma out 1 act.( 14.320770 sig in 25 act.) RANK 15 NODE 18 --> 10.806815 sigma out 1 act.( 12.905733 sig in 25 act.) RANK 16 NODE 5 --> 10.030907 sigma out 1 act.( 13.612177 sig in 25 act.) RANK 17 NODE 10 --> 9.9335079 sigma out 1 act.( 13.246193 sig in 25 act.) RANK 18 NODE 25 --> 9.7138214 sigma out 1 act.( 12.778802 sig in 25 act.) RANK 19 NODE 12 --> 9.4851799 sigma out 1 act.( 11.047687 sig in 25 act.) RANK 20 NODE 1 --> 7.7275672 sigma out 1 act.( 8.9254675 sig in 25 act.) RANK 21 NODE 16 --> 7.6304274 sigma out 1 act.( 9.9734564 sig in 25 act.) RANK 22 NODE 4 --> 6.0752950 sigma out 1 act.( 9.5003529 sig in 25 act.) RANK 23 NODE 14 --> 5.3386607 sigma out 1 act.( 9.1558723 sig in 25 act.) RANK 24 NODE 11 --> 5.0188622 sigma out 1 act.( 10.283065 sig in 25 act.) RANK 25 NODE 3 --> 4.8866148 sigma out 1 act.( 8.6352177 sig in 25 act.) RANK 26 NODE 2 --> 3.4494467 sigma out 1 act.( 8.1367912 sig in 25 act.) RANK 1 NODE 1 --> 131.26085 sigma in 26 active inputs *********************************************** *** Learn Path 10 *** loss function: -0.67212951 *** contribution from regularisation: 9.09617229E-04 *** contribution from error: -0.67303914 *** contribution from DIAG: 2.04842354E-06 *********************************************** --------------------------------------------------- Iteration : 11 *********************************************** *** Learn Path 11 *** loss function: -0.67213231 *** contribution from regularisation: 9.06847825E-04 *** contribution from error: -0.67303914 *** contribution from DIAG: 2.04264416E-06 *********************************************** --------------------------------------------------- Iteration : 12 *********************************************** *** Learn Path 12 *** loss function: -0.67213136 *** contribution from regularisation: 9.07788286E-04 *** contribution from error: -0.67303914 *** contribution from DIAG: 2.03779359E-06 *********************************************** --------------------------------------------------- Iteration : 100 SIGNIFICANCE OF OUTPUTS IN LAYER 1 RANK 1 NODE 1 --> 97.129593 sigma out 26 active outputs RANK 2 NODE 2 --> 26.988163 sigma out 26 active outputs RANK 3 NODE 8 --> 22.496922 sigma out 26 active outputs RANK 4 NODE 5 --> 21.012583 sigma out 26 active outputs RANK 5 NODE 6 --> 17.581991 sigma out 26 active outputs RANK 6 NODE 7 --> 16.831974 sigma out 26 active outputs RANK 7 NODE 3 --> 16.808083 sigma out 26 active outputs RANK 8 NODE 4 --> 16.192106 sigma out 26 active outputs RANK 9 NODE 9 --> 16.098759 sigma out 26 active outputs RANK 10 NODE 13 --> 13.657197 sigma out 26 active outputs RANK 11 NODE 17 --> 11.538003 sigma out 26 active outputs RANK 12 NODE 10 --> 11.361193 sigma out 26 active outputs RANK 13 NODE 12 --> 10.868420 sigma out 26 active outputs RANK 14 NODE 18 --> 10.190662 sigma out 26 active outputs RANK 15 NODE 16 --> 10.151620 sigma out 26 active outputs RANK 16 NODE 15 --> 9.6305847 sigma out 26 active outputs RANK 17 NODE 14 --> 9.3421755 sigma out 26 active outputs RANK 18 NODE 22 --> 8.8623657 sigma out 26 active outputs RANK 19 NODE 19 --> 8.7690210 sigma out 26 active outputs RANK 20 NODE 21 --> 7.7608938 sigma out 26 active outputs RANK 21 NODE 20 --> 7.4959311 sigma out 26 active outputs RANK 22 NODE 11 --> 7.1315894 sigma out 26 active outputs RANK 23 NODE 23 --> 6.3984275 sigma out 26 active outputs RANK 24 NODE 24 --> 4.4617424 sigma out 26 active outputs RANK 25 NODE 25 --> 3.9716358 sigma out 26 active outputs SIGNIFICANCE OF INPUTS TO LAYER 2 sorted by input significance RANK 1 NODE 19 --> 60.351055 sigma in 25 act. ( 74.367950 sig out 1 act.) RANK 2 NODE 8 --> 48.513340 sigma in 25 act. ( 69.781143 sig out 1 act.) RANK 3 NODE 24 --> 33.253250 sigma in 25 act. ( 31.247692 sig out 1 act.) RANK 4 NODE 13 --> 32.145741 sigma in 25 act. ( 39.693554 sig out 1 act.) RANK 5 NODE 21 --> 28.770803 sigma in 25 act. ( 29.020452 sig out 1 act.) RANK 6 NODE 20 --> 27.362898 sigma in 25 act. ( 21.498173 sig out 1 act.) RANK 7 NODE 23 --> 24.298901 sigma in 25 act. ( 24.230625 sig out 1 act.) RANK 8 NODE 7 --> 22.725494 sigma in 25 act. ( 18.665178 sig out 1 act.) RANK 9 NODE 6 --> 18.485243 sigma in 25 act. ( 16.816420 sig out 1 act.) RANK 10 NODE 9 --> 17.447674 sigma in 25 act. ( 16.274662 sig out 1 act.) RANK 11 NODE 22 --> 16.466448 sigma in 25 act. ( 15.968657 sig out 1 act.) RANK 12 NODE 15 --> 16.284792 sigma in 25 act. ( 18.709223 sig out 1 act.) RANK 13 NODE 26 --> 15.164739 sigma in 25 act. ( 14.966593 sig out 1 act.) RANK 14 NODE 17 --> 14.449580 sigma in 25 act. ( 11.933581 sig out 1 act.) RANK 15 NODE 5 --> 13.715751 sigma in 25 act. ( 9.9614105 sig out 1 act.) RANK 16 NODE 10 --> 13.368304 sigma in 25 act. ( 9.8055687 sig out 1 act.) RANK 17 NODE 18 --> 12.926034 sigma in 25 act. ( 10.872544 sig out 1 act.) RANK 18 NODE 25 --> 12.731705 sigma in 25 act. ( 9.9936152 sig out 1 act.) RANK 19 NODE 12 --> 11.081096 sigma in 25 act. ( 9.5167503 sig out 1 act.) RANK 20 NODE 11 --> 10.309916 sigma in 25 act. ( 5.0369096 sig out 1 act.) RANK 21 NODE 16 --> 10.015307 sigma in 25 act. ( 7.7082343 sig out 1 act.) RANK 22 NODE 4 --> 9.4643297 sigma in 25 act. ( 6.1767097 sig out 1 act.) RANK 23 NODE 14 --> 9.1630182 sigma in 25 act. ( 5.3767776 sig out 1 act.) RANK 24 NODE 1 --> 8.9530678 sigma in 25 act. ( 7.7460322 sig out 1 act.) RANK 25 NODE 3 --> 8.6275778 sigma in 25 act. ( 4.9392004 sig out 1 act.) RANK 26 NODE 2 --> 8.1566305 sigma in 25 act. ( 3.3844354 sig out 1 act.) sorted by output significance RANK 1 NODE 19 --> 74.367950 sigma out 1 act.( 60.351055 sig in 25 act.) RANK 2 NODE 8 --> 69.781143 sigma out 1 act.( 48.513340 sig in 25 act.) RANK 3 NODE 13 --> 39.693554 sigma out 1 act.( 32.145741 sig in 25 act.) RANK 4 NODE 24 --> 31.247692 sigma out 1 act.( 33.253250 sig in 25 act.) RANK 5 NODE 21 --> 29.020452 sigma out 1 act.( 28.770803 sig in 25 act.) RANK 6 NODE 23 --> 24.230625 sigma out 1 act.( 24.298901 sig in 25 act.) RANK 7 NODE 20 --> 21.498173 sigma out 1 act.( 27.362898 sig in 25 act.) RANK 8 NODE 15 --> 18.709223 sigma out 1 act.( 16.284792 sig in 25 act.) RANK 9 NODE 7 --> 18.665178 sigma out 1 act.( 22.725494 sig in 25 act.) RANK 10 NODE 6 --> 16.816420 sigma out 1 act.( 18.485243 sig in 25 act.) RANK 11 NODE 9 --> 16.274662 sigma out 1 act.( 17.447674 sig in 25 act.) RANK 12 NODE 22 --> 15.968657 sigma out 1 act.( 16.466448 sig in 25 act.) RANK 13 NODE 26 --> 14.966593 sigma out 1 act.( 15.164739 sig in 25 act.) RANK 14 NODE 17 --> 11.933581 sigma out 1 act.( 14.449580 sig in 25 act.) RANK 15 NODE 18 --> 10.872544 sigma out 1 act.( 12.926034 sig in 25 act.) RANK 16 NODE 25 --> 9.9936152 sigma out 1 act.( 12.731705 sig in 25 act.) RANK 17 NODE 5 --> 9.9614105 sigma out 1 act.( 13.715751 sig in 25 act.) RANK 18 NODE 10 --> 9.8055687 sigma out 1 act.( 13.368304 sig in 25 act.) RANK 19 NODE 12 --> 9.5167503 sigma out 1 act.( 11.081096 sig in 25 act.) RANK 20 NODE 1 --> 7.7460322 sigma out 1 act.( 8.9530678 sig in 25 act.) RANK 21 NODE 16 --> 7.7082343 sigma out 1 act.( 10.015307 sig in 25 act.) RANK 22 NODE 4 --> 6.1767097 sigma out 1 act.( 9.4643297 sig in 25 act.) RANK 23 NODE 14 --> 5.3767776 sigma out 1 act.( 9.1630182 sig in 25 act.) RANK 24 NODE 11 --> 5.0369096 sigma out 1 act.( 10.309916 sig in 25 act.) RANK 25 NODE 3 --> 4.9392004 sigma out 1 act.( 8.6275778 sig in 25 act.) RANK 26 NODE 2 --> 3.3844354 sigma out 1 act.( 8.1566305 sig in 25 act.) RANK 1 NODE 1 --> 132.14650 sigma in 26 active inputs *********************************************** *** Learn Path 100 *** loss function: -0.67213351 *** contribution from regularisation: 9.05624067E-04 *** contribution from error: -0.67303914 *** contribution from DIAG: 1.97947475E-06 *********************************************** -----------------> Test sample END OF LEARNING , export EXPERTISE WRITE NETWORK WEIGHTS TO EXPERTISE NB_AHITOUT: storage space 73262 Training Complete :) Network Config file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/GlobalPID_Muon_Upstream_ANN.txt Training parameters file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/train-config.txt Input Data file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/datafiles.txt Neurobayes parameters file = /afs/cern.ch/user/j/jonrob/cmtuser/Brunel_HEAD/Rec/ChargedProtoANNPIDTeacher/training/results/MC12/TrainKeepGhosts-EvalKeepGhosts-NaturalMix/NoPreSels-WithGECs/DIAG/ENTROPY/LD1/BFGS/621/Muon/Upstream/NB.txt Training Host = lxplus432.cern.ch Particle type = muon Background types = all Training Mix = NaturalMix Track type = Upstream Track PresSel = TrackPreSelNone Network type = NeuroBayes Ghost treatment = Ghosts Ghosts Min P = 0 MeV/c Min Pt = 0 MeV/c Max Chi^2 = 10 Min likelihood = -100 Max Ghost Prob = 1 Output file = GlobalPID_Muon_Upstream_NeuroBayes.conf Skipping input #RichUsedR2Gas Skipping input #RichAboveElThres Skipping input #RichAbovePiThres Skipping input #RichAbovePrThres Training ROOT file /castor/cern.ch/user/j/jonrob/ProtoParticlePIDtuples/MC12-Binc-nu2.5/Reco13d.root Evaluation ROOT file /castor/cern.ch/user/j/jonrob/ProtoParticlePIDtuples/MC12-Binc-nu2.5/Reco13a.root Training sample size = 1000000 Evaluation sample size = 5000000 Node layer two scale = 1.2 Input layer has 23 nodes, hidden layer has 26 nodes NB_DEF_TASK = CLA NB_DEF_MOM = 0 NB_DEF_REG = ALL NB_DEF_LOSS = ENTROPY NB_DEF_METHOD = BFGS NB_DEF_SHAPE = DIAG NB_DEF_LEARNDIAG = 1 NB_DEF_PRE = 621 Attempting to open training ROOT file /castor/cern.ch/user/j/jonrob/ProtoParticlePIDtuples/MC12-Binc-nu2.5/Reco13d.root Found 5016459 training data points Read entry 501645 (9.99998%) Read entry 1003290 (20%) Read entry 1504935 (29.9999%) Read entry 2006580 (39.9999%) Read entry 2508225 (49.9999%) Read entry 3009870 (59.9999%) Read entry 3511515 (69.9999%) Read entry 4013160 (79.9999%) Read entry 4514805 (89.9998%) Read entry 5016450 (99.9998%) Considered 5016459 tracks for input to NN training Sel. Eff. = 15.3957% Selected 772320 tracks for input to NN training ghost percentage = 31.254% electron percentage = 4.90095% muon percentage = 0.306868% pion percentage = 53.4443% kaon percentage = 7.06508% Unknown Particle type 411 percentage = 0.00038844% Unknown Particle type 431 percentage = 0.00012948% Unknown Particle type 521 percentage = 0.00012948% proton percentage = 2.93674% Unknown Particle type 3112 percentage = 0.0337943% Unknown Particle type 3222 percentage = 0.0280972% Unknown Particle type 3312 percentage = 0.0130775% Unknown Particle type 3334 percentage = 0.00077688% Unknown Particle type 1000010020 percentage = 0.00246012% Unknown Particle type 1000010030 percentage = 0.00297804% Unknown Particle type 1000020040 percentage = 0.0102289% Making plots for input NumProtoParticles Creating ROOT directory NNcut0.025 Creating ROOT directory NNcut0.050 Creating ROOT directory NNcut0.075 Creating ROOT directory NNcut0.100 Creating ROOT directory NNcut0.125 Creating ROOT directory NNcut0.150 Creating ROOT directory NNcut0.175 Creating ROOT directory NNcut0.200 Creating ROOT directory NNcut0.350 Creating ROOT directory NNcut0.500 Creating ROOT directory NNcut0.750 Creating ROOT directory NNcut0.900 Creating ROOT directory DLLcut-6.000 Creating ROOT directory DLLcut-5.500 Creating ROOT directory DLLcut-5.000 Creating ROOT directory DLLcut-4.500 Creating ROOT directory DLLcut-4.000 Creating ROOT directory DLLcut-3.500 Creating ROOT directory DLLcut-3.000 Creating ROOT directory DLLcut-2.500 Creating ROOT directory DLLcut-2.000 Creating ROOT directory DLLcut-1.500 Creating ROOT directory DLLcut-1.000 Creating ROOT directory DLLcut-0.500 Creating ROOT directory DLLcut0.000 Creating ROOT directory DLLcut0.500 Creating ROOT directory DLLcut1.000 Creating ROOT directory DLLcut1.500 Creating ROOT directory DLLcut2.000 Creating ROOT directory DLLcut2.500 Creating ROOT directory DLLcut3.000 Creating ROOT directory DLLcut3.500 Creating ROOT directory DLLcut4.000 Creating ROOT directory DLLcut4.500 Creating ROOT directory DLLcut5.000 Creating ROOT directory DLLcut5.500 Creating ROOT directory DLLcut6.000 Making plots for input TrackP Making plots for input TrackPt Making plots for input TrackChi2PerDof Making plots for input TrackNumDof Making plots for input TrackLikelihood Making plots for input TrackGhostProbability Making plots for input TrackCloneDist Making plots for input TrackFitVeloChi2 Making plots for input TrackFitVeloNDoF Making plots for input RichUsedAero Making plots for input RichUsedR1Gas Making plots for input RichAboveMuThres Making plots for input RichAboveKaThres Making plots for input RichDLLe Making plots for input RichDLLmu Making plots for input RichDLLk Making plots for input RichDLLp Making plots for input RichDLLbt Making plots for input InAccBrem Making plots for input BremPIDe Making plots for input VeloCharge Attempting to open evaluation ROOT file /castor/cern.ch/user/j/jonrob/ProtoParticlePIDtuples/MC12-Binc-nu2.5/Reco13a.root Found 2528565 evaluation data points Read entry 252856 (9.99998%) Read entry 505712 (20%) Read entry 758568 (29.9999%) Read entry 1011424 (39.9999%) Read entry 1264280 (49.9999%) Read entry 1517136 (59.9999%) Read entry 1769992 (69.9999%) Read entry 2022848 (79.9998%) Read entry 2275704 (89.9998%) Read entry 2528560 (99.9998%) Making final performance plots ... Finished... asciiToRoot: converting ahist.txt to Root format ... finished Found 22 input variables. ***************Training results***************** number of nodes in the 1st layer: 25 number of nodes in the 2nd layer: 26 number of nodes in the 3rd layer: 1 number of iterations: 100