Execution Time3.72s

Test: gtest-tmva-tmva-test-envelope-TMVA-Classification (Passed)
Build: master-x86_64-centos7-clang100-opt-no-rt-cxxmodules (olsnba08.cern.ch) on 2019-11-14 01:39:53
Repository revision: 32b17abcda23e44b64218a42d0ca69cb30cda7e0

Test Timing: Passed
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Test output
Running main() from gtest_main.cc
[==========] Running 2 tests from 2 test cases.
[----------] Global test environment set-up.
[----------] 1 test from ClassifierTest1
[ RUN      ] ClassifierTest1.BasicTests
[TFile::Cp] Total 0.20 MB	|>...................| 0.00 % [0.0 MB/s][TFile::Cp] Total 0.20 MB	|====================| 100.00 % [33.3 MB/s]
Info in <TFile::OpenFromCache>: using local cache copy of http://root.cern.ch/files/tmva_class_example.root [./files/tmva_class_example.root]
create data set info dataset
DataSetInfo              : [dataset] : Added class "Signal"
                         : Add Tree TreeS of type Signal with 6000 events
DataSetInfo              : [dataset] : Added class "Background"
                         : Add Tree TreeB of type Background with 6000 events
<HEADER>                          : Loading booked method: BDT BDTB
                         : 
                         : Building event vectors for type 2 Signal
                         : Dataset[dataset] :  create input formulas for tree TreeS
                         : Building event vectors for type 2 Background
                         : Dataset[dataset] :  create input formulas for tree TreeB
<HEADER> DataSetFactory           : [dataset] : Number of events in input trees
                         : 
                         : 
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 1000
                         : Signal     -- testing events             : 5000
                         : Signal     -- training and testing events: 6000
                         : Background -- training events            : 1000
                         : Background -- testing events             : 5000
                         : Background -- training and testing events: 6000
                         : 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ----------------------------------------
                         :           myvar1  myvar2    var3    var4
                         :  myvar1:  +1.000  -0.039  +0.778  +0.931
                         :  myvar2:  -0.039  +1.000  -0.111  +0.033
                         :    var3:  +0.778  -0.111  +1.000  +0.860
                         :    var4:  +0.931  +0.033  +0.860  +1.000
                         : ----------------------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ----------------------------------------
                         :           myvar1  myvar2    var3    var4
                         :  myvar1:  +1.000  +0.033  +0.784  +0.931
                         :  myvar2:  +0.033  +1.000  -0.014  +0.112
                         :    var3:  +0.784  -0.014  +1.000  +0.863
                         :    var4:  +0.931  +0.112  +0.863  +1.000
                         : ----------------------------------------
<HEADER> DataSetFactory           : [dataset] :  
                         : 
<HEADER>                          : Training method BDT BDTB
<HEADER>                          : Train method: BDTB for Classification
                         : 
<HEADER> BDTB                     : #events: (reweighted) sig: 1000 bkg: 1000
                         : #events: (unweighted) sig: 1000 bkg: 1000
                         : Training 100 Decision Trees ... patience please
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                         : Elapsed time for training with 2000 events: 0.125 sec         
<HEADER> BDTB                     : [dataset] : Evaluation of BDTB on training sample (2000 events)
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                         : Elapsed time for evaluation of 2000 events: 0.012 sec       
                         : Creating xml weight file: dataset/weights/Classification_BDTB.weights.xml
                         : Creating standalone class: dataset/weights/Classification_BDTB.class.C
<HEADER>                          : Training finished
                         : 
<HEADER>                          : Test all methods
<HEADER>                          : Test method: BDTB for Classification performance
                         : 
<HEADER> BDTB                     : [dataset] : Evaluation of BDTB on testing sample (10000 events)
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                         : Elapsed time for evaluation of 10000 events: 0.0518 sec       
<HEADER>                          : Evaluate classifier: BDTB
                         : 
<HEADER> BDTB                     : [dataset] : Loop over test events and fill histograms with classifier response...
                         : 
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : dataset       BDTB           : 0.854
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : dataset              BDTB           : 0.000 (0.000)       0.620 (0.641)      0.844 (0.864)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER>                          : Loading booked method: BDT BDTG
                         : 
<HEADER>                          : Training method BDT BDTG
<HEADER>                          : Train method: BDTG for Classification
                         : 
<HEADER> BDTG                     : #events: (reweighted) sig: 1000 bkg: 1000
                         : #events: (unweighted) sig: 1000 bkg: 1000
                         : Training 100 Decision Trees ... patience please
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                         : Elapsed time for training with 2000 events: 0.168 sec         
<HEADER> BDTG                     : [dataset] : Evaluation of BDTG on training sample (2000 events)
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                         : Elapsed time for evaluation of 2000 events: 0.0142 sec       
                         : Creating xml weight file: dataset/weights/Classification_BDTG.weights.xml
                         : Creating standalone class: dataset/weights/Classification_BDTG.class.C
<HEADER>                          : Training finished
                         : 
<HEADER>                          : Test all methods
<HEADER>                          : Test method: BDTG for Classification performance
                         : 
<HEADER> BDTG                     : [dataset] : Evaluation of BDTG on testing sample (10000 events)
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                         : Elapsed time for evaluation of 10000 events: 0.0668 sec       
<HEADER>                          : Evaluate classifier: BDTG
                         : 
<HEADER> BDTG                     : [dataset] : Loop over test events and fill histograms with classifier response...
                         : 
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : dataset       BDTG           : 0.898
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : dataset              BDTG           : 0.259 (0.527)       0.705 (0.800)      0.903 (0.927)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
[       OK ] ClassifierTest1.BasicTests (2612 ms)
[----------] 1 test from ClassifierTest1 (2612 ms total)

[----------] 1 test from ClassifierTest2
[ RUN      ] ClassifierTest2.TestsOverOutput
Info in <TFile::OpenFromCache>: using local cache copy of http://root.cern.ch/files/tmva_class_example.root [./files/tmva_class_example.root]
create data set info dataset
<HEADER> DataSetInfo              : [dataset] : Added class "Signal"
                         : Add Tree TreeS of type Signal with 6000 events
<HEADER> DataSetInfo              : [dataset] : Added class "Background"
                         : Add Tree TreeB of type Background with 6000 events
<HEADER>                          : Loading booked method: BDT BDTB
                         : 
                         : Building event vectors for type 2 Signal
                         : Dataset[dataset] :  create input formulas for tree TreeS
                         : Building event vectors for type 2 Background
                         : Dataset[dataset] :  create input formulas for tree TreeB
<HEADER> DataSetFactory           : [dataset] : Number of events in input trees
                         : 
                         : 
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 1000
                         : Signal     -- testing events             : 5000
                         : Signal     -- training and testing events: 6000
                         : Background -- training events            : 1000
                         : Background -- testing events             : 5000
                         : Background -- training and testing events: 6000
                         : 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ----------------------------------------
                         :           myvar1  myvar2    var3    var4
                         :  myvar1:  +1.000  -0.039  +0.778  +0.931
                         :  myvar2:  -0.039  +1.000  -0.111  +0.033
                         :    var3:  +0.778  -0.111  +1.000  +0.860
                         :    var4:  +0.931  +0.033  +0.860  +1.000
                         : ----------------------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ----------------------------------------
                         :           myvar1  myvar2    var3    var4
                         :  myvar1:  +1.000  +0.033  +0.784  +0.931
                         :  myvar2:  +0.033  +1.000  -0.014  +0.112
                         :    var3:  +0.784  -0.014  +1.000  +0.863
                         :    var4:  +0.931  +0.112  +0.863  +1.000
                         : ----------------------------------------
<HEADER> DataSetFactory           : [dataset] :  
                         : 
<HEADER>                          : Training method BDT BDTB
<HEADER>                          : Train method: BDTB for Classification
                         : 
<HEADER> BDTB                     : #events: (reweighted) sig: 1000 bkg: 1000
                         : #events: (unweighted) sig: 1000 bkg: 1000
                         : Training 100 Decision Trees ... patience please
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                         : Elapsed time for training with 2000 events: 0.1 sec         
<HEADER> BDTB                     : [dataset] : Evaluation of BDTB on training sample (2000 events)
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                         : Elapsed time for evaluation of 2000 events: 0.0125 sec       
                         : Creating xml weight file: dataset/weights/Classification_BDTB.weights.xml
                         : Creating standalone class: dataset/weights/Classification_BDTB.class.C
                         : TMVAtmp1.root:/dataset/Method_BDT/BDTB
<HEADER>                          : Training finished
                         : 
<HEADER>                          : Test all methods
<HEADER>                          : Test method: BDTB for Classification performance
                         : 
<HEADER> BDTB                     : [dataset] : Evaluation of BDTB on testing sample (10000 events)
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                         : Elapsed time for evaluation of 10000 events: 0.0543 sec       
<HEADER>                          : Evaluate classifier: BDTB
                         : 
<HEADER> BDTB                     : [dataset] : Loop over test events and fill histograms with classifier response...
                         : 
<HEADER> TFHandler_BDTB           : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :   myvar1:    0.20301     1.7142   [    -9.8605     7.9024 ]
                         :   myvar2:  -0.048747     1.1049   [    -4.0854     4.0291 ]
                         :     var3:    0.15975     1.0530   [    -5.3563     4.6430 ]
                         :     var4:    0.42792     1.2213   [    -6.9675     5.0307 ]
                         : -----------------------------------------------------------
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : dataset       BDTB           : 0.854
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : dataset              BDTB           : 0.000 (0.000)       0.620 (0.641)      0.844 (0.864)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Dataset:dataset          : Created tree 'TestTree' with 10000 events
                         : 
<HEADER> Dataset:dataset          : Created tree 'TrainTree' with 2000 events
                         : 
[       OK ] ClassifierTest2.TestsOverOutput (911 ms)
[----------] 1 test from ClassifierTest2 (911 ms total)

[----------] Global test environment tear-down
[==========] 2 tests from 2 test cases ran. (3524 ms total)
[  PASSED  ] 2 tests.