Execution Time16.12s

Test: tutorial-tmva-TMVARegression (Passed)
Build: v6-18-00-patches-x86_64-ubuntu16-gcc54-opt (sft-ubuntu-1604-4) on 2019-11-14 00:46:47
Repository revision: 869553a4dd0f00a0fc618d6e9d1fbdd66c820707

Test Timing: Passed
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Test output
Processing /mnt/build/night/LABEL/ROOT-ubuntu16/SPEC/cxx14/V/6-18/root/tutorials/tmva/TMVARegression.C...

==> Start TMVARegression
[TFile::Cp] Total 0.11 MB	|>...................| 0.00 % [0.0 MB/s][TFile::Cp] Total 0.11 MB	|====================| 100.00 % [27.3 MB/s]
Info in <TFile::OpenFromCache>: using local cache copy of http://root.cern.ch/files/tmva_reg_example.root [./files/tmva_reg_example.root]
--- TMVARegression           : Using input file: ./files/tmva_reg_example.root
DataSetInfo              : [dataset] : Added class "Regression"
                         : Add Tree TreeR of type Regression with 10000 events
                         : Dataset[dataset] : Class index : 0  name : Regression
Factory                  : Booking method: [NON-XML-CHAR-0x1B][1mPDEFoam[NON-XML-CHAR-0x1B][0m
                         : 
DataSetFactory           : [dataset] : Number of events in input trees
                         : 
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Regression -- training events            : 1000
                         : Regression -- testing events             : 9000
                         : Regression -- training and testing events: 10000
                         : 
DataSetInfo              : Correlation matrix (Regression):
                         : ------------------------
                         :             var1    var2
                         :    var1:  +1.000  -0.018
                         :    var2:  -0.018  +1.000
                         : ------------------------
DataSetFactory           : [dataset] :  
                         : 
Factory                  : Booking method: [NON-XML-CHAR-0x1B][1mKNN[NON-XML-CHAR-0x1B][0m
                         : 
Factory                  : Booking method: [NON-XML-CHAR-0x1B][1mLD[NON-XML-CHAR-0x1B][0m
                         : 
Factory                  : Booking method: [NON-XML-CHAR-0x1B][1mDNN_CPU[NON-XML-CHAR-0x1B][0m
                         : 
                         : Parsing option string: 
                         : ... "!H:V:ErrorStrategy=SUMOFSQUARES:VarTransform=G:WeightInitialization=XAVIERUNIFORM:Architecture=CPU:Layout=TANH|50,Layout=TANH|50,Layout=TANH|50,LINEAR:TrainingStrategy=LearningRate=1e-2,Momentum=0.5,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=10,WeightDecay=0.01,Regularization=NONE,DropConfig=0.2+0.2+0.2+0.,DropRepetitions=2|LearningRate=1e-3,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=L2,DropConfig=0.1+0.1+0.1,DropRepetitions=1|LearningRate=1e-4,Momentum=0.3,Repetitions=1,ConvergenceSteps=10,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=NONE"
                         : The following options are set:
                         : - By User:
                         :     <none>
                         : - Default:
                         :     Boost_num: "0" [Number of times the classifier will be boosted]
                         : Parsing option string: 
                         : ... "!H:V:ErrorStrategy=SUMOFSQUARES:VarTransform=G:WeightInitialization=XAVIERUNIFORM:Architecture=CPU:Layout=TANH|50,Layout=TANH|50,Layout=TANH|50,LINEAR:TrainingStrategy=LearningRate=1e-2,Momentum=0.5,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=10,WeightDecay=0.01,Regularization=NONE,DropConfig=0.2+0.2+0.2+0.,DropRepetitions=2|LearningRate=1e-3,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=L2,DropConfig=0.1+0.1+0.1,DropRepetitions=1|LearningRate=1e-4,Momentum=0.3,Repetitions=1,ConvergenceSteps=10,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=NONE"
                         : The following options are set:
                         : - By User:
                         :     V: "True" [Verbose output (short form of "VerbosityLevel" below - overrides the latter one)]
                         :     VarTransform: "G" [List of variable transformations performed before training, e.g., "D_Background,P_Signal,G,N_AllClasses" for: "Decorrelation, PCA-transformation, Gaussianisation, Normalisation, each for the given class of events ('AllClasses' denotes all events of all classes, if no class indication is given, 'All' is assumed)"]
                         :     H: "False" [Print method-specific help message]
                         :     Layout: "TANH|50,Layout=TANH|50,Layout=TANH|50,LINEAR" [Layout of the network.]
                         :     ErrorStrategy: "SUMOFSQUARES" [Loss function: Mean squared error (regression) or cross entropy (binary classification).]
                         :     WeightInitialization: "XAVIERUNIFORM" [Weight initialization strategy]
                         :     Architecture: "CPU" [Which architecture to perform the training on.]
                         :     TrainingStrategy: "LearningRate=1e-2,Momentum=0.5,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=10,WeightDecay=0.01,Regularization=NONE,DropConfig=0.2+0.2+0.2+0.,DropRepetitions=2|LearningRate=1e-3,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=L2,DropConfig=0.1+0.1+0.1,DropRepetitions=1|LearningRate=1e-4,Momentum=0.3,Repetitions=1,ConvergenceSteps=10,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=NONE" [Defines the training strategies.]
                         : - Default:
                         :     VerbosityLevel: "Default" [Verbosity level]
                         :     CreateMVAPdfs: "False" [Create PDFs for classifier outputs (signal and background)]
                         :     IgnoreNegWeightsInTraining: "False" [Events with negative weights are ignored in the training (but are included for testing and performance evaluation)]
                         :     ValidationSize: "20%" [Part of the training data to use for validation. Specify as 0.2 or 20% to use a fifth of the data set as validation set. Specify as 100 to use exactly 100 events. (Default: 20%)]
DNN_CPU                  : [dataset] : Create Transformation "G" with events from all classes.
                         : 
                         : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Preparing the Gaussian transformation...
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.013183     1.0272   [    -3.3668     5.7307 ]
                         :     var2:  0.0071633     1.0351   [    -4.2630     5.7307 ]
                         :   fvalue:     164.96     82.203   [     1.7144     391.23 ]
                         : -----------------------------------------------------------
Parsed Training DNN string LearningRate=1e-2,Momentum=0.5,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=10,WeightDecay=0.01,Regularization=NONE,DropConfig=0.2+0.2+0.2+0.,DropRepetitions=2|LearningRate=1e-3,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=L2,DropConfig=0.1+0.1+0.1,DropRepetitions=1|LearningRate=1e-4,Momentum=0.3,Repetitions=1,ConvergenceSteps=10,BatchSize=50,TestRepetitions=5,WeightDecay=0.01,Regularization=NONE
STring has size 3
Factory                  : Booking method: [NON-XML-CHAR-0x1B][1mBDTG[NON-XML-CHAR-0x1B][0m
                         : 
<WARNING>                : Value for option maxdepth was previously set to 3
                         : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad
                         : --> change to new default NegWeightTreatment=Pray
Factory                  : [NON-XML-CHAR-0x1B][1mTrain all methods[NON-XML-CHAR-0x1B][0m
Factory                  : [dataset] : Create Transformation "I" with events from all classes.
                         : 
                         : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.4138     1.1963   [  0.0026062     4.9957 ]
                         :     var2:     2.4356     1.4134   [  0.0092062     4.9990 ]
                         :   fvalue:     164.96     82.203   [     1.7144     391.23 ]
                         : -----------------------------------------------------------
                         : Ranking input variables (method unspecific)...
IdTransformation         : Ranking result (top variable is best ranked)
                         : --------------------------------------------
                         : Rank : Variable  : |Correlation with target|
                         : --------------------------------------------
                         :    1 : var2      : 7.419e-01
                         :    2 : var1      : 5.996e-01
                         : --------------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : -------------------------------------
                         : Rank : Variable  : Mutual information
                         : -------------------------------------
                         :    1 : var2      : 2.029e+00
                         :    2 : var1      : 1.950e+00
                         : -------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : ------------------------------------
                         : Rank : Variable  : Correlation Ratio
                         : ------------------------------------
                         :    1 : var1      : 6.538e+00
                         :    2 : var2      : 2.460e+00
                         : ------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : ----------------------------------------
                         : Rank : Variable  : Correlation Ratio (T)
                         : ----------------------------------------
                         :    1 : var2      : 9.156e-01
                         :    2 : var1      : 2.981e-01
                         : ----------------------------------------
Factory                  : Train method: PDEFoam for Regression
                         : 
                         : Build mono target regression foam
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                         : Elapsed time: 0.676 sec                                 
                         : Elapsed time for training with 1000 events: 0.683 sec         
                         : Dataset[dataset] : Create results for training
                         : Dataset[dataset] : Evaluation of PDEFoam on training sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 1000 events: 0.00588 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
                         : Creating xml weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_PDEFoam.weights.xml[NON-XML-CHAR-0x1B][0m
                         : writing foam MonoTargetRegressionFoam to file
                         : Foams written to file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_PDEFoam.weights_foams.root[NON-XML-CHAR-0x1B][0m
Factory                  : Training finished
                         : 
Factory                  : Train method: KNN for Regression
                         : 
KNN                      : <Train> start...
                         : Reading 1000 events
                         : Number of signal events 1000
                         : Number of background events 0
                         : Creating kd-tree with 1000 events
                         : Computing scale factor for 1d distributions: (ifrac, bottom, top) = (80%, 10%, 90%)
ModulekNN                : Optimizing tree for 2 variables with 1000 values
                         : <Fill> Class 1 has     1000 events
                         : Elapsed time for training with 1000 events: 0.00154 sec         
                         : Dataset[dataset] : Create results for training
                         : Dataset[dataset] : Evaluation of KNN on training sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 1000 events: 0.0202 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
                         : Creating xml weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_KNN.weights.xml[NON-XML-CHAR-0x1B][0m
Factory                  : Training finished
                         : 
Factory                  : Train method: LD for Regression
                         : 
LD                       : Results for LD coefficients:
                         : -----------------------
                         : Variable:  Coefficient:
                         : -----------------------
                         :     var1:      +42.104
                         :     var2:      +44.607
                         : (offset):      -87.420
                         : -----------------------
                         : Elapsed time for training with 1000 events: 0.00055 sec         
                         : Dataset[dataset] : Create results for training
                         : Dataset[dataset] : Evaluation of LD on training sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 1000 events: 0.00167 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
                         : Creating xml weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_LD.weights.xml[NON-XML-CHAR-0x1B][0m
Factory                  : Training finished
                         : 
Factory                  : Train method: DNN_CPU for Regression
                         : 
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.013183     1.0272   [    -3.3668     5.7307 ]
                         :     var2:  0.0071633     1.0351   [    -4.2630     5.7307 ]
                         :   fvalue:     164.96     82.203   [     1.7144     391.23 ]
                         : -----------------------------------------------------------
                         : Start of neural network training on CPU.
                         : 
                         : Training phase 1 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :         10 |      1366.52     1336.24      3.7794           0
                         :         20 |      776.015     639.871     3.37517           0
                         :         30 |      735.326     780.317      4.3855          10
                         :         40 |      1289.67     1418.03     4.44614          20
                         : 
                         : Training phase 2 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      4043.62     580.013       4.503           0
                         :         10 |      4061.38     766.712     4.51147           5
                         :         15 |      3875.67     437.981     4.50487           0
                         :         20 |      3874.47     697.469     4.49562           5
                         :         25 |      3966.71     575.026     4.49463          10
                         :         30 |         3869     642.057     4.49788          15
                         :         35 |      3836.63     676.906     4.49975          20
                         : 
                         : Training phase 3 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      617.014      583.53     5.19426           0
                         :         10 |       595.79     549.916     5.18479           0
                         :         15 |      582.183     534.717     5.18498           0
                         :         20 |      572.431     525.354     5.18124           0
                         :         25 |      552.837      515.86     5.17918           0
                         :         30 |      539.849     507.543     5.17851           0
                         :         35 |      531.908     501.598     5.18198           0
                         :         40 |      522.784     496.019     5.18662           0
                         :         45 |      513.399     490.858     5.18263           0
                         :         50 |      507.889     485.817      5.1848           0
                         :         55 |      502.018     479.603     5.17683           0
                         :         60 |      494.989      470.78      5.1823           0
                         :         65 |      489.525     466.091     5.17788           0
                         :         70 |      483.441     462.583     5.18867           0
                         :         75 |      474.706     459.447     5.18263           0
                         :         80 |      472.531     456.686     5.18636           0
                         :         85 |      467.832     453.732      5.1499           0
                         :         90 |      464.394     450.743     5.18291           0
                         :         95 |      460.395     447.606     5.17428           0
                         :        100 |       457.65     445.469      5.1749           0
                         :        105 |      453.979      443.63     5.18474           0
                         :        110 |      450.873     440.309     5.18283           0
                         :        115 |      447.344     438.094     5.19151           0
                         :        120 |      443.606     435.168      5.1943           0
                         :        125 |       440.66     431.966     5.18731           0
                         :        130 |      435.096     422.331     5.19556           0
                         :        135 |      431.951     418.184     4.98092           0
                         :        140 |      427.481     413.953      5.0004           0
                         :        145 |      423.813     412.053     5.18258           0
                         :        150 |      421.017     408.855     5.19762           0
                         :        155 |      418.928     406.927     5.15566           0
                         :        160 |      416.412      403.88      5.1883           0
                         :        165 |      415.353     401.974     5.19636           0
                         :        170 |      414.771     401.058     5.18795           0
                         :        175 |      409.515     398.931     5.19596           0
                         :        180 |      410.081     398.979     5.19767           5
                         :        185 |      405.167     395.664     5.19544           0
                         :        190 |      403.706     394.206     5.13492           0
                         :        195 |      402.947      393.57     5.18451           0
                         :        200 |      400.486     391.579     5.18036           0
                         :        205 |      399.952     390.994     5.18723           0
                         :        210 |      398.837     389.707     5.01331           0
                         :        215 |      396.373     388.341     5.19057           0
                         :        220 |      396.921     388.072     5.19261           5
                         :        225 |      393.687     386.546     5.17081           0
                         :        230 |      392.647     385.938     5.17909           0
                         :        235 |      391.099     385.256     5.19063           0
                         :        240 |      389.412     384.228     5.19219           0
                         :        245 |      387.852      383.24     5.19228           0
                         :        250 |      385.759     382.245     5.18441           0
                         :        255 |       384.45     381.057     5.15126           0
                         :        260 |      383.091     380.534      5.1613           0
                         :        265 |      381.989     379.983     5.16906           0
                         :        270 |       380.52      379.53      5.1814           0
                         :        275 |      379.559     378.482     5.18506           0
                         :        280 |       378.39     376.695     5.19026           0
                         :        285 |      380.413     377.656     5.18905           5
                         :        290 |      376.983     375.108     5.18828           0
                         :        295 |      375.313     373.414     5.19793           0
                         :        300 |      373.501     371.573     5.17109           0
                         :        305 |      372.316     370.844     5.19495           0
                         :        310 |      370.801     370.081     5.18729           0
                         :        315 |      370.024     369.282       5.191           0
                         :        320 |       371.76     369.917     5.19328           5
                         :        325 |      368.034     367.162       5.181           0
                         :        330 |      367.323     367.029     5.18334           5
                         :        335 |      366.345       365.3     5.18704           0
                         :        340 |      365.971     364.887     5.15755           0
                         :        345 |       364.91     363.528     5.17971           0
                         :        350 |       363.77     362.086     5.18357           0
                         :        355 |       363.19       361.6     5.17981           0
                         :        360 |      362.686      360.09     5.18487           0
                         :        365 |      361.847     359.684     5.19163           0
                         :        370 |      361.695     357.704     5.18964           0
                         :        375 |      360.293     357.636     5.18956           5
                         :        380 |      360.179     356.158     5.19105           0
                         :        385 |      358.503     355.132     5.18911           0
                         :        390 |       357.14     352.731     5.19336           0
                         :        395 |      355.705     350.777     5.18954           0
                         :        400 |      354.603     349.781      5.1884           0
                         :        405 |      353.533     349.016     5.19796           0
                         :        410 |      352.352     349.666     5.19941           5
                         :        415 |      351.293     347.651     5.19549           0
                         :        420 |      350.734     346.665     5.19006           0
                         :        425 |      349.809     347.342     5.19714           5
                         :        430 |      348.902     346.813     5.17393          10
                         : 
                         : Elapsed time for training with 1000 events: 2.66 sec         
                         : Dataset[dataset] : Create results for training
                         : Dataset[dataset] : Evaluation of DNN_CPU on training sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 1000 events: 0.023 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
                         : Creating xml weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_DNN_CPU.weights.xml[NON-XML-CHAR-0x1B][0m
Factory                  : Training finished
                         : 
Factory                  : Train method: BDTG for Regression
                         : 
                         : Regression Loss Function: Huber
                         : Training 2000 Decision Trees ... patience please
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                         : Elapsed time for training with 1000 events: 1.61 sec         
                         : Dataset[dataset] : Create results for training
                         : Dataset[dataset] : Evaluation of BDTG on training sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 1000 events: 0.327 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
                         : Creating xml weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_BDTG.weights.xml[NON-XML-CHAR-0x1B][0m
Factory                  : Training finished
                         : 
Factory                  : === Destroy and recreate all methods via weight files for testing ===
                         : 
                         : Reading weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_PDEFoam.weights.xml[NON-XML-CHAR-0x1B][0m
                         : Read foams from file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_PDEFoam.weights_foams.root[NON-XML-CHAR-0x1B][0m
                         : Reading weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_KNN.weights.xml[NON-XML-CHAR-0x1B][0m
                         : Creating kd-tree with 1000 events
                         : Computing scale factor for 1d distributions: (ifrac, bottom, top) = (80%, 10%, 90%)
ModulekNN                : Optimizing tree for 2 variables with 1000 values
                         : <Fill> Class 1 has     1000 events
                         : Reading weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_LD.weights.xml[NON-XML-CHAR-0x1B][0m
                         : Reading weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_DNN_CPU.weights.xml[NON-XML-CHAR-0x1B][0m
                         : Reading weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVARegression_BDTG.weights.xml[NON-XML-CHAR-0x1B][0m
Factory                  : [NON-XML-CHAR-0x1B][1mTest all methods[NON-XML-CHAR-0x1B][0m
Factory                  : Test method: PDEFoam for Regression performance
                         : 
                         : Dataset[dataset] : Create results for testing
                         : Dataset[dataset] : Evaluation of PDEFoam on testing sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 9000 events: 0.0473 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
Factory                  : Test method: KNN for Regression performance
                         : 
                         : Dataset[dataset] : Create results for testing
                         : Dataset[dataset] : Evaluation of KNN on testing sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 9000 events: 0.0757 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
Factory                  : Test method: LD for Regression performance
                         : 
                         : Dataset[dataset] : Create results for testing
                         : Dataset[dataset] : Evaluation of LD on testing sample
                         : Dataset[dataset] : Elapsed time for evaluation of 9000 events: 0.00464 sec       
                         : Create variable histograms
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                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
Factory                  : Test method: DNN_CPU for Regression performance
                         : 
                         : Dataset[dataset] : Create results for testing
                         : Dataset[dataset] : Evaluation of DNN_CPU on testing sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 9000 events: 0.197 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
Factory                  : Test method: BDTG for Regression performance
                         : 
                         : Dataset[dataset] : Create results for testing
                         : Dataset[dataset] : Evaluation of BDTG on testing sample
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                         : Dataset[dataset] : Elapsed time for evaluation of 9000 events: 1.98 sec       
                         : Create variable histograms
                         : Create regression target histograms
                         : Create regression average deviation
                         : Results created
Factory                  : [NON-XML-CHAR-0x1B][1mEvaluate all methods[NON-XML-CHAR-0x1B][0m
                         : Evaluate regression method: PDEFoam
                         : TestRegression (testing)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 9000 events: 0.0457 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.00547 sec       
TFHandler_PDEFoam        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3309     1.1858   [ 0.00020069     5.0000 ]
                         :     var2:     2.4914     1.4393   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.02     83.932   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
                         : Evaluate regression method: KNN
                         : TestRegression (testing)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 9000 events: 0.0737 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.00841 sec       
TFHandler_KNN            : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3309     1.1858   [ 0.00020069     5.0000 ]
                         :     var2:     2.4914     1.4393   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.02     83.932   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
                         : Evaluate regression method: LD
                         : TestRegression (testing)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 9000 events: 0.00646 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.000991 sec       
TFHandler_LD             : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3309     1.1858   [ 0.00020069     5.0000 ]
                         :     var2:     2.4914     1.4393   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.02     83.932   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
                         : Evaluate regression method: DNN_CPU
                         : TestRegression (testing)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 9000 events: 0.195 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.0216 sec       
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:  -0.062720     1.0031   [    -3.3827     5.7307 ]
                         :     var2:   0.031261     1.0685   [    -5.7307     5.7307 ]
                         :   fvalue:     164.02     83.932   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:  -0.062720     1.0031   [    -3.3827     5.7307 ]
                         :     var2:   0.031261     1.0685   [    -5.7307     5.7307 ]
                         :   fvalue:     164.02     83.932   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
                         : Evaluate regression method: BDTG
                         : TestRegression (testing)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 9000 events: 1.97 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.221 sec       
TFHandler_BDTG           : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3309     1.1858   [ 0.00020069     5.0000 ]
                         :     var2:     2.4914     1.4393   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.02     83.932   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
                         : 
                         : Evaluation results ranked by smallest RMS on test sample:
                         : ("Bias" quotes the mean deviation of the regression from true target.
                         :  "MutInf" is the "Mutual Information" between regression and target.
                         :  Indicated by "_T" are the corresponding "truncated" quantities ob-
                         :  tained when removing events deviating more than 2sigma from average.)
                         : --------------------------------------------------------------------------------------------------
                         : --------------------------------------------------------------------------------------------------
                         : dataset              BDTG           :    0.252    0.209     2.27     1.83  |  3.137  3.210
                         : dataset              KNN            :   -0.507    0.436     5.77     3.79  |  2.871  2.903
                         : dataset              PDEFoam        :   -0.831   -0.645     9.90     8.12  |  2.245  2.327
                         : dataset              DNN_CPU        :    0.642     1.23     19.8     16.1  |  1.731  1.820
                         : dataset              LD             :  -0.0644     1.63     19.7     17.9  |  1.988  1.981
                         : --------------------------------------------------------------------------------------------------
                         : 
                         : Evaluation results ranked by smallest RMS on training sample:
                         : (overtraining check)
                         : --------------------------------------------------------------------------------------------------
                         : DataSet Name:         MVA Method:        <Bias>   <Bias_T>    RMS    RMS_T  |  MutInf MutInf_T
                         : --------------------------------------------------------------------------------------------------
                         : dataset              BDTG           :   0.0373-0.000948    0.483    0.255  |  3.435  3.459
                         : dataset              KNN            :   -0.523    0.298     5.55     3.82  |  2.931  2.946
                         : dataset              PDEFoam        : 7.41e-07    0.243     7.99     6.37  |  2.489  2.565
                         : dataset              DNN_CPU        :    0.279     1.19     18.7     15.0  |  1.902  1.994
                         : dataset              LD             : 3.68e-06     1.76     18.9     16.9  |  2.101  2.099
                         : --------------------------------------------------------------------------------------------------
                         : 
Dataset:dataset          : Created tree 'TestTree' with 9000 events
                         : 
Dataset:dataset          : Created tree 'TrainTree' with 1000 events
                         : 
Factory                  : [NON-XML-CHAR-0x1B][1mThank you for using TMVA![NON-XML-CHAR-0x1B][0m
                         : [NON-XML-CHAR-0x1B][1mFor citation information, please visit: http://tmva.sf.net/citeTMVA.html[NON-XML-CHAR-0x1B][0m
==> Wrote root file: TMVAReg.root
==> TMVARegression is done!