Execution Time33.84s

Test: tutorial-tmva-TMVARegression (Passed)
Build: master-x86_64-mac1013-clang100 (macphsft16.dyndns.cern.ch) on 2019-11-14 00:49:58

Test Timing: Passed
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Test output
Processing /Users/sftnight/build/jenkins/night/LABEL/mac1013/SPEC/cxx14/V/master/root/tutorials/tmva/TMVARegression.C...

==> Start TMVARegression
create data set info dataset
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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
                         : 
                         : Building event vectors for type 2 Regression
                         : Dataset[dataset] :  create input formulas for tree TreeR
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  +0.000
                         :    var2:  +0.000  +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:   0.012881     1.0268   [    -3.3375     5.7307 ]
                         :     var2: -0.0084074     1.0227   [    -3.3854     5.7307 ]
                         :   fvalue:     161.52     84.040   [     1.7144     386.62 ]
                         : -----------------------------------------------------------
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:     3.3187     1.1824   [  0.0010317     4.9985 ]
                         :     var2:     2.4362     1.4606   [  0.0039980     4.9910 ]
                         :   fvalue:     161.52     84.040   [     1.7144     386.62 ]
                         : -----------------------------------------------------------
                         : Ranking input variables (method unspecific)...
IdTransformation         : Ranking result (top variable is best ranked)
                         : --------------------------------------------
                         : Rank : Variable  : |Correlation with target|
                         : --------------------------------------------
                         :    1 : var2      : 7.598e-01
                         :    2 : var1      : 5.804e-01
                         : --------------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : -------------------------------------
                         : Rank : Variable  : Mutual information
                         : -------------------------------------
                         :    1 : var1      : 1.629e+00
                         :    2 : var2      : 1.488e+00
                         : -------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : ------------------------------------
                         : Rank : Variable  : Correlation Ratio
                         : ------------------------------------
                         :    1 : var1      : 6.004e+00
                         :    2 : var2      : 2.486e+00
                         : ------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : ----------------------------------------
                         : Rank : Variable  : Correlation Ratio (T)
                         : ----------------------------------------
                         :    1 : var2      : 1.117e+00
                         :    2 : var1      : 4.783e-01
                         : ----------------------------------------
Factory                  : Train method: PDEFoam for Regression
                         : 
                         : Build mono target regression foam
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                         : Elapsed time: 2.65 sec                                 
                         : Elapsed time for training with 1000 events: 2.67 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: 0.0151 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: 0.00679 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: 0.0289 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:      +42.357
                         :     var2:      +44.121
                         : (offset):      -86.539
                         : -----------------------
                         : Elapsed time for training with 1000 events: 0.000908 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: 0.00352 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:   0.012881     1.0268   [    -3.3375     5.7307 ]
                         :     var2: -0.0084074     1.0227   [    -3.3854     5.7307 ]
                         :   fvalue:     161.52     84.040   [     1.7144     386.62 ]
                         : -----------------------------------------------------------
                         : Start of neural network training on CPU.
                         : 
                         : Training phase 1 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :         10 |      655.749      1092.6     3.37561           0
                         :         20 |      1091.83     1547.91     3.34889          10
                         :         30 |      1140.95     1534.28     2.96394          20
                         : 
                         : Training phase 2 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      2434.24      1136.3     3.39824           0
                         :         10 |      2370.89     1083.93     4.03286           0
                         :         15 |      2519.61     1198.95     3.40662           5
                         :         20 |      2788.39     1863.07      3.2449          10
                         :         25 |      2454.22     1238.92     3.38878          15
                         :         30 |         2677     1660.38     1.92525          20
                         : 
                         : Training phase 3 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      707.488     1336.37     2.60508           0
                         :         10 |      664.978     1238.21     2.82923           0
                         :         15 |      648.814     1190.26     3.07573           0
                         :         20 |      634.754     1160.97      3.1118           0
                         :         25 |      626.031     1139.79     3.10201           0
                         :         30 |      617.231     1120.25     3.20313           0
                         :         35 |      607.809     1100.35     3.85641           0
                         :         40 |       601.78      1095.8     3.68577           0
                         :         45 |      593.932     1082.17     2.77872           0
                         :         50 |      589.256     1066.55     3.02406           0
                         :         55 |      585.948     1058.69     3.86001           0
                         :         60 |      583.282     1054.73     3.53783           0
                         :         65 |      580.463     1046.77     4.25869           0
                         :         70 |      578.561     1032.75     4.37157           0
                         :         75 |      576.359     1026.33     3.12409           0
                         :         80 |      573.359     1026.05     3.24464           5
                         :         85 |      571.118     1017.85     2.89108           0
                         :         90 |      569.389     1011.69     1.73208           0
                         :         95 |        567.7     1007.86     3.44623           0
                         :        100 |      566.116     1003.18     3.02907           0
                         :        105 |      565.676     995.102     3.16542           0
                         :        110 |      567.517     990.923     3.33052           0
                         :        115 |      563.297     987.689     3.23543           0
                         :        120 |      560.216     985.429     3.43708           0
                         :        125 |      559.231     979.734     4.38005           0
                         :        130 |      559.192      983.87     4.36098           5
                         :        135 |      558.694     971.357     4.03417           0
                         :        140 |      556.067     968.965     4.44813           0
                         :        145 |      554.332     969.937     4.61989           5
                         :        150 |      554.939     962.908     4.42689           0
                         :        155 |      552.782      966.84     3.66651           5
                         :        160 |      553.554     955.084     3.99511           0
                         :        165 |      549.844      954.11     3.68807           0
                         :        170 |      548.873     950.865     3.94761           0
                         :        175 |      548.651     947.812     3.99948           0
                         :        180 |      547.584     952.227     3.08897           5
                         :        185 |      546.103     947.008     2.52613          10
                         : 
                         : Elapsed time for training with 1000 events: 2 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: 0.0719 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: 5.18 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: 0.702 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
                         : TMVAReg.root:/dataset/Method_BDT/BDTG
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: 0.132 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: 0.24 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
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                         : Dataset[dataset] : Elapsed time for evaluation of 9000 events: 0.0224 sec       
                         : Create variable histograms
                         : 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: 0.507 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: 4.82 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: 0.126 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.0144 sec       
TFHandler_PDEFoam        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3418     1.1876   [ 0.00020069     5.0000 ]
                         :     var2:     2.4912     1.4340   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.41     83.720   [     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: 0.235 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.0267 sec       
TFHandler_KNN            : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3418     1.1876   [ 0.00020069     5.0000 ]
                         :     var2:     2.4912     1.4340   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.41     83.720   [     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: 0.0172 sec       
                         : TestRegression (training)
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                         : Elapsed time for evaluation of 1000 events: 0.00173 sec       
TFHandler_LD             : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3418     1.1876   [ 0.00020069     5.0000 ]
                         :     var2:     2.4912     1.4340   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.41     83.720   [     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: 0.472 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.0542 sec       
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.016886     1.0107   [    -3.3420     5.7307 ]
                         :     var2:   0.034670    0.99482   [    -5.7307     5.7307 ]
                         :   fvalue:     164.41     83.720   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.016886     1.0107   [    -3.3420     5.7307 ]
                         :     var2:   0.034670    0.99482   [    -5.7307     5.7307 ]
                         :   fvalue:     164.41     83.720   [     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: 5.42 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.622 sec       
TFHandler_BDTG           : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3418     1.1876   [ 0.00020069     5.0000 ]
                         :     var2:     2.4912     1.4340   [ 0.00071490     5.0000 ]
                         :   fvalue:     164.41     83.720   [     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           :    0.198    0.165     2.60     2.00  |  3.084  3.149
                         : dataset              KNN            :   -0.436    0.361     5.57     3.89  |  2.833  2.887
                         : dataset              PDEFoam        :   -0.388   -0.453     10.4     8.41  |  2.234  2.323
                         : dataset              LD             :    0.512     2.21     19.7     17.7  |  1.986  1.976
                         : dataset              DNN_CPU        :    -1.67    0.601     24.9     19.6  |  1.505  1.549
                         : --------------------------------------------------------------------------------------------------
                         : 
                         : 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           :   0.0445  0.00997    0.463    0.233  |  3.445  3.482
                         : dataset              KNN            :   -0.696    0.100     5.52     3.79  |  2.918  2.947
                         : dataset              PDEFoam        :-6.61e-07   0.0554     8.22     6.37  |  2.482  2.589
                         : dataset              LD             : 2.12e-06     1.65     20.0     18.1  |  2.086  2.077
                         : dataset              DNN_CPU        :    -1.30     1.35     25.0     19.6  |  1.588  1.607
                         : --------------------------------------------------------------------------------------------------
                         : 
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!