Execution Time40.50s

Test: tutorial-tmva-TMVARegression (Passed)
Build: master-x86_64-centos7-gcc62-opt-no-rt-cxxmodules (olsnba08.cern.ch) on 2019-11-14 01:02:24
Repository revision: 32b17abcda23e44b64218a42d0ca69cb30cda7e0

Test Timing: Passed
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Test output
Processing /data/sftnight/workspace/root-benchmark-no-rt-cxxmodules/BUILDTYPE/Release/COMPILER/gcc62/LABEL/performance-sandy-cc7/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  -0.018
                         :    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: 1.18 sec                                 
                         : Elapsed time for training with 1000 events: 1.19 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: 0.00944 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: 0.00329 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: 0.0118 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: 0.00096 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: 0.00425 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 |      1296.97     1421.93    0.234435           0
                         :         20 |       1291.6        1149    0.237469           0
                         :         30 |      996.427     981.044    0.242786           0
                         :         40 |      2436.68      2195.6    0.246431          10
                         :         50 |      915.832     956.905    0.203524           0
                         :         60 |      2404.63     2043.84    0.248165          10
                         :         70 |      1952.26     1994.92    0.245598          20
                         : 
                         : Training phase 2 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      17216.6     837.769     0.24792           0
                         :         10 |      16733.8     939.247    0.239354           5
                         :         15 |      16167.7     585.158    0.196548           0
                         :         20 |      15882.3     703.632    0.218071           5
                         :         25 |      15330.7      778.91    0.242157          10
                         :         30 |      14870.4     872.532    0.271185          15
                         :         35 |        14579     962.518    0.252502          20
                         : 
                         : Training phase 3 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      894.154     923.635    0.273637           0
                         :         10 |      859.367     901.753    0.251998           0
                         :         15 |      831.362     881.462    0.249582           0
                         :         20 |      807.009     866.739    0.256246           0
                         :         25 |      782.722     851.308    0.266586           0
                         :         30 |      765.527     842.134    0.244402           0
                         :         35 |      753.379     836.313    0.251729           0
                         :         40 |      743.421     831.726    0.259451           0
                         :         45 |      735.019     828.729    0.246725           0
                         :         50 |      727.866     826.308    0.274195           0
                         :         55 |       721.66     824.517    0.242182           0
                         :         60 |      716.428     823.127    0.241806           0
                         :         65 |       711.87     822.364    0.258194           5
                         :         70 |      707.661     822.154    0.260895           0
                         :         75 |      704.575     821.562    0.244423           5
                         :         80 |      701.485     820.982    0.250895           0
                         :         85 |      698.753     820.913    0.247406           5
                         :         90 |      695.959     821.133    0.209588          10
                         : 
                         : Elapsed time for training with 1000 events: 21.1 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: 0.0439 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: 2.38 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: 0.339 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: 0.0787 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: 0.12 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: 0.0103 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: 0.372 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: 2.15 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: 0.0751 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.00886 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: 0.113 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.0132 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: 0.00908 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.00145 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: 0.359 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.0359 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: 3.16 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.5 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              LD             :  -0.0644     1.63     19.7     17.9  |  1.988  1.981
                         : dataset              DNN_CPU        :    0.485     2.75     28.2     22.5  |  1.390  1.482
                         : --------------------------------------------------------------------------------------------------
                         : 
                         : 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              LD             : 3.68e-06     1.76     18.9     16.9  |  2.101  2.099
                         : dataset              DNN_CPU        :    0.410     2.73     26.8     21.8  |  1.458  1.548
                         : --------------------------------------------------------------------------------------------------
                         : 
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!