Execution Time17.08s

Test: tutorial-tmva-TMVARegression (Passed)
Build: master-x86_64-fedora28-gcc8 (sft-fedora-28-1.cern.ch) on 2019-11-14 01:14:20

Test Timing: Passed
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Test output
Processing /mnt/build/night/LABEL/ROOT-fedora28/SPEC/soversion/V/master/root/tutorials/tmva/TMVARegression.C...

==> Start TMVARegression
create data set info dataset
[TFile::Cp] Total 0.11 MB	|>...................| 0.00 % [0.0 MB/s][TFile::Cp] Total 0.11 MB	|====================| 100.00 % [31.9 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
                         : 
                         : 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  +0.006
                         :    var2:  +0.006  +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:   0.012586     1.0260   [    -3.3377     5.7307 ]
                         :     var2:  0.0043504     1.0383   [    -4.5564     5.7307 ]
                         :   fvalue:     165.93     84.643   [     2.0973     391.01 ]
                         : -----------------------------------------------------------
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:     3.3759     1.1674   [  0.0058046     4.9975 ]
                         :     var2:     2.4823     1.4587   [  0.0032142     4.9971 ]
                         :   fvalue:     165.93     84.643   [     2.0973     391.01 ]
                         : -----------------------------------------------------------
                         : Ranking input variables (method unspecific)...
IdTransformation         : Ranking result (top variable is best ranked)
                         : --------------------------------------------
                         : Rank : Variable  : |Correlation with target|
                         : --------------------------------------------
                         :    1 : var2      : 7.636e-01
                         :    2 : var1      : 5.936e-01
                         : --------------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : -------------------------------------
                         : Rank : Variable  : Mutual information
                         : -------------------------------------
                         :    1 : var2      : 2.315e+00
                         :    2 : var1      : 1.882e+00
                         : -------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : ------------------------------------
                         : Rank : Variable  : Correlation Ratio
                         : ------------------------------------
                         :    1 : var1      : 6.545e+00
                         :    2 : var2      : 2.414e+00
                         : ------------------------------------
IdTransformation         : Ranking result (top variable is best ranked)
                         : ----------------------------------------
                         : Rank : Variable  : Correlation Ratio (T)
                         : ----------------------------------------
                         :    1 : var2      : 8.189e-01
                         :    2 : var1      : 3.128e-01
                         : ----------------------------------------
Factory                  : Train method: PDEFoam for Regression
                         : 
                         : Build mono target regression foam
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                         : Elapsed time: 0.63 sec                                 
                         : Elapsed time for training with 1000 events: 0.638 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: 0.006 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: 0.00191 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: 0.00934 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:      +42.509
                         :     var2:      +44.738
                         : (offset):      -88.627
                         : -----------------------
                         : Elapsed time for training with 1000 events: 0.00092 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: 0.00202 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:   0.012586     1.0260   [    -3.3377     5.7307 ]
                         :     var2:  0.0043504     1.0383   [    -4.5564     5.7307 ]
                         :   fvalue:     165.93     84.643   [     2.0973     391.01 ]
                         : -----------------------------------------------------------
                         : Start of neural network training on CPU.
                         : 
                         : Training phase 1 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :         10 |      1435.47     1289.95     7.38899           0
                         :         20 |      1602.01     1429.42     7.93248          10
                         :         30 |      2054.68     1500.55     8.03535          20
                         : 
                         : Training phase 2 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      5639.42     1155.14     8.61903           0
                         :         10 |      5295.21     1243.58     8.65899           5
                         :         15 |      5630.99     1594.98     8.69729          10
                         :         20 |      4920.84     951.835     8.77009           0
                         :         25 |       5571.3     2211.38     8.75909           5
                         :         30 |      5174.44     1526.34     8.78975          10
                         :         35 |      5545.04     1875.19     8.83353          15
                         :         40 |      9164.52     3115.92     8.83339          20
                         : 
                         : Training phase 3 of 3:
                         :      Epoch |   Train Err.  Test  Err.     GFLOP/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |      2335.43     2516.41     12.2362           0
                         :         10 |      2301.07     2460.42     11.8473           0
                         :         15 |       2273.4     2420.93     12.3312           0
                         :         20 |      2247.79     2387.56     12.4456           0
                         :         25 |      2223.42     2357.52     12.1726           0
                         :         30 |       2200.4     2327.86     12.4677           0
                         :         35 |      2178.44     2300.74     12.3743           0
                         :         40 |      2157.49     2275.04     12.4784           0
                         :         45 |      2137.57     2248.94     12.4437           0
                         :         50 |       2118.5     2223.92     12.3311           0
                         :         55 |      2100.47     2201.26     12.4514           0
                         :         60 |      2083.24     2179.34     11.6755           0
                         :         65 |      2066.85     2158.08     11.7344           0
                         :         70 |      2051.22     2137.87     12.0124           0
                         :         75 |      2036.35     2118.08     12.0835           0
                         :         80 |      2022.11     2098.75      8.4947           0
                         :         85 |      2008.54     2080.25     12.3799           0
                         :         90 |      1995.69     2063.67     12.0671           0
                         :         95 |      1983.38     2047.38     12.4195           0
                         :        100 |      1971.66     2030.65     12.3719           0
                         :        105 |      1960.44     2014.84     12.3149           0
                         :        110 |      1949.78     1999.93     11.3261           0
                         :        115 |       1939.6     1986.02     12.3553           0
                         :        120 |      1929.89     1972.41     12.2918           0
                         :        125 |      1920.61     1959.29     12.3634           0
                         :        130 |      1911.74     1946.94     11.9338           0
                         :        135 |      1903.31     1934.54     11.0866           0
                         :        140 |      1895.23     1923.34     11.6809           0
                         :        145 |       1887.5     1912.16     12.0916           0
                         :        150 |      1880.11     1901.55     11.7174           0
                         :        155 |      1873.08     1891.09     11.8441           0
                         :        160 |      1866.35     1880.98     12.4106           0
                         :        165 |      1859.89      1871.4     11.6499           0
                         :        170 |      1853.72     1861.44     12.2417           0
                         :        175 |      1847.84     1852.54     11.3316           0
                         :        180 |       1842.2     1844.04     12.4472           0
                         :        185 |      1836.79     1835.86     12.3725           0
                         :        190 |      1831.61     1827.92      12.422           0
                         :        195 |      1826.67      1820.5      12.388           0
                         :        200 |      1821.92      1812.7     12.4835           0
                         :        205 |      1817.38     1805.72     10.2718           0
                         :        210 |      1813.04     1798.72     12.5209           0
                         :        215 |      1808.83     1791.49     12.3289           0
                         :        220 |      1804.82     1785.53     12.4233           0
                         :        225 |      1800.98     1779.31     12.3157           0
                         :        230 |      1797.28     1773.38     12.4018           0
                         :        235 |      1793.74     1767.63     12.4506           0
                         :        240 |      1790.34     1761.93     12.3595           0
                         :        245 |      1787.07     1756.47     12.1428           0
                         :        250 |      1783.93     1750.91     12.4763           0
                         :        255 |       1780.9     1746.38     12.4871           0
                         :        260 |         1778     1741.67     12.4373           0
                         :        265 |       1775.2     1736.32     12.4558           0
                         :        270 |      1772.51     1731.68     12.3342           0
                         :        275 |      1769.92     1727.82     12.4972           0
                         :        280 |      1767.42        1724     12.2825           0
                         :        285 |      1765.02     1718.92     12.4882           0
                         :        290 |       1762.7     1714.83     12.4127           0
                         :        295 |      1760.45     1711.12     12.4614           0
                         :        300 |      1758.29     1707.57     9.83742           0
                         :        305 |      1756.21     1704.06     12.4441           0
                         :        310 |      1754.21     1700.16     12.3622           0
                         :        315 |      1752.25     1696.84     12.3684           0
                         :        320 |      1750.37     1693.95      12.435           0
                         :        325 |      1748.55     1690.72     12.2844           0
                         :        330 |      1746.79      1687.7     12.4992           0
                         :        335 |      1745.09     1684.76     12.0296           0
                         :        340 |      1743.44     1682.12     12.3827           0
                         :        345 |      1741.81     1678.58     12.2318           0
                         :        350 |      1740.22     1675.73      12.382           0
                         :        355 |      1738.49        1673     12.4429           0
                         :        360 |      1752.33     1673.36     12.4822           5
                         :        365 |      1746.92     1673.78     12.3796          10
                         : 
                         : Elapsed time for training with 1000 events: 1.05 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: 0.0243 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: 1.89 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: 0.389 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: 0.0806 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: 0.0845 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: 0.0044 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: 0.21 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: 2.37 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: 0.0488 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.00579 sec       
TFHandler_PDEFoam        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3352     1.1893   [ 0.00020069     5.0000 ]
                         :     var2:     2.4860     1.4342   [ 0.00071490     5.0000 ]
                         :   fvalue:     163.91     83.651   [     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: 0.0865 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.00956 sec       
TFHandler_KNN            : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3352     1.1893   [ 0.00020069     5.0000 ]
                         :     var2:     2.4860     1.4342   [ 0.00071490     5.0000 ]
                         :   fvalue:     163.91     83.651   [     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: 0.00655 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.000976 sec       
TFHandler_LD             : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3352     1.1893   [ 0.00020069     5.0000 ]
                         :     var2:     2.4860     1.4342   [ 0.00071490     5.0000 ]
                         :   fvalue:     163.91     83.651   [     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: 0.208 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.0223 sec       
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:  -0.027278     1.0264   [    -3.3694     5.7307 ]
                         :     var2:  0.0056047    0.98632   [    -5.7307     5.7307 ]
                         :   fvalue:     163.91     83.651   [     1.6186     394.84 ]
                         : -----------------------------------------------------------
TFHandler_DNN_CPU        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:  -0.027278     1.0264   [    -3.3694     5.7307 ]
                         :     var2:  0.0056047    0.98632   [    -5.7307     5.7307 ]
                         :   fvalue:     163.91     83.651   [     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: 2.4 sec       
                         : TestRegression (training)
                         : Calculate regression for all events
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                         : Elapsed time for evaluation of 1000 events: 0.276 sec       
TFHandler_BDTG           : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:     3.3352     1.1893   [ 0.00020069     5.0000 ]
                         :     var2:     2.4860     1.4342   [ 0.00071490     5.0000 ]
                         :   fvalue:     163.91     83.651   [     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           :   0.0707    0.102     2.45     1.95  |  3.100  3.175
                         : dataset              KNN            :   -0.237    0.578     5.17     3.44  |  2.898  2.939
                         : dataset              PDEFoam        :    0.106  -0.0677     9.22     7.74  |  2.283  2.375
                         : dataset              LD             :    0.461     2.22     19.6     17.6  |  1.985  1.979
                         : dataset              DNN_CPU        :   -0.145     2.84     40.6     35.9  |  0.810  0.911
                         : --------------------------------------------------------------------------------------------------
                         : 
                         : 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           :   0.0597   0.0107    0.566    0.293  |  3.441  3.466
                         : dataset              KNN            :   -0.425    0.423     5.19     3.54  |  3.006  3.034
                         : dataset              PDEFoam        : 8.35e-07    0.106     8.04     6.57  |  2.488  2.579
                         : dataset              LD             :-1.03e-06     1.54     20.1     18.5  |  2.134  2.153
                         : dataset              DNN_CPU        :   -0.319     1.32     41.6     37.2  |  0.828  0.903
                         : --------------------------------------------------------------------------------------------------
                         : 
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!