Execution Time47.89s

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

Test Timing: Passed
Processors1

Show Command Line
Display graphs:

Test output
Processing /Users/sftnight/build/jenkins/night/LABEL/mac1013/SPEC/cxx14/V/master/root/tutorials/tmva/TMVAMultipleBackgroundExample.C...
Start Test TMVAGAexample
========================

... event: 0 (200)
======> EVENT:0
 var1            = -1.14361
 var2            = -0.822373
 var3            = -0.395426
 var4            = -0.529427
created tree: TreeS
... event: 0 (200)
======> EVENT:0
 var1            = -1.54361
 var2            = -1.42237
 var3            = -1.39543
 var4            = -2.02943
created tree: TreeB0
... event: 0 (200)
======> EVENT:0
 var1            = -1.54361
 var2            = -0.822373
 var3            = -0.395426
 var4            = -2.02943
created tree: TreeB1
======> EVENT:0
 var1            = 0.463304
 var2            = 1.37192
 var3            = -1.16769
 var4            = -1.77551
created tree: TreeB2
created data file: tmva_example_multiple_background.root

========================
--- Training
create data set info datasetBkg0
<HEADER> DataSetInfo              : [datasetBkg0] : Added class "Signal"
                         : Add Tree TreeS of type Signal with 200 events
<HEADER> DataSetInfo              : [datasetBkg0] : Added class "Background"
                         : Add Tree TreeB0 of type Background with 200 events
<HEADER> Factory                  : Booking method: BDTG
                         : 
                         : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad
                         : --> change to new default NegWeightTreatment=Pray
                         : Building event vectors for type 2 Signal
                         : Dataset[datasetBkg0] :  create input formulas for tree TreeS
                         : Building event vectors for type 2 Background
                         : Dataset[datasetBkg0] :  create input formulas for tree TreeB0
<HEADER> DataSetFactory           : [datasetBkg0] : Number of events in input trees
                         : 
                         : 
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 100
                         : Signal     -- testing events             : 100
                         : Signal     -- training and testing events: 200
                         : Background -- training events            : 100
                         : Background -- testing events             : 100
                         : Background -- training and testing events: 200
                         : 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  +0.303  +0.518  +0.811
                         :    var2:  +0.303  +1.000  +0.747  +0.724
                         :    var3:  +0.518  +0.747  +1.000  +0.825
                         :    var4:  +0.811  +0.724  +0.825  +1.000
                         : ----------------------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  +0.274  +0.597  +0.826
                         :    var2:  +0.274  +1.000  +0.682  +0.644
                         :    var3:  +0.597  +0.682  +1.000  +0.847
                         :    var4:  +0.826  +0.644  +0.847  +1.000
                         : ----------------------------------------
<HEADER> DataSetFactory           : [datasetBkg0] :  
                         : 
<HEADER> Factory                  : Train all methods
<HEADER> Factory                  : [datasetBkg0] : Create Transformation "I" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg0] : Create Transformation "D" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg0] : Create Transformation "P" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg0] : Create Transformation "G" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg0] : Create Transformation "D" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.083014    0.94480   [    -2.7150     2.1743 ]
                         :     var2:   0.072289    0.93344   [    -2.8854     2.5106 ]
                         :     var3:    0.16043     1.0325   [    -2.1404     3.3281 ]
                         :     var4:    0.28995     1.1531   [    -2.6365     3.5074 ]
                         : -----------------------------------------------------------
                         : Preparing the Decorrelation transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:  -0.074036     1.0000   [    -3.4110     2.5953 ]
                         :     var2:  -0.052209     1.0000   [    -3.0414     1.9842 ]
                         :     var3:   0.027631     1.0000   [    -2.1476     3.4355 ]
                         :     var4:    0.35174     1.0000   [    -2.6534     2.6418 ]
                         : -----------------------------------------------------------
                         : Preparing the Principle Component (PCA) transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1: 7.3062e-09     1.7774   [    -3.9398     5.1856 ]
                         :     var2:-4.5169e-10    0.81293   [    -2.0944     1.7698 ]
                         :     var3:-1.1898e-09    0.47498   [    -1.3801     1.2627 ]
                         :     var4: 4.7963e-10    0.33741   [   -0.82442    0.71800 ]
                         : -----------------------------------------------------------
                         : Preparing the Gaussian transformation...
                         : Preparing the Decorrelation transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:    0.19308     1.0000   [    -1.4198     5.9167 ]
                         :     var2:    0.15726     1.0000   [    -1.8259     4.9943 ]
                         :     var3:    0.11942     1.0000   [    -2.0954     6.4037 ]
                         :     var4:   0.024613     1.0000   [    -2.8761     4.5862 ]
                         : -----------------------------------------------------------
                         : Ranking input variables (method unspecific)...
<HEADER> IdTransformation         : Ranking result (top variable is best ranked)
                         : -----------------------------------
                         : Rank : Variable   : Separation
                         : -----------------------------------
                         :    1 : Variable 4 : 3.527e-01
                         :    2 : Variable 3 : 2.743e-01
                         :    3 : Variable 1 : 1.869e-01
                         :    4 : Variable 2 : 1.239e-01
                         : -----------------------------------
<HEADER> Factory                  : Train method: BDTG for Classification
                         : 
<HEADER> BDTG                     : #events: (reweighted) sig: 100 bkg: 100
                         : #events: (unweighted) sig: 100 bkg: 100
                         : Training 1000 Decision Trees ... patience please
0%, time left: unknown
6%, time left: 0 sec
12%, time left: 0 sec
18%, time left: 0 sec
25%, time left: 0 sec
31%, time left: 0 sec
37%, time left: 0 sec
43%, time left: 0 sec
50%, time left: 0 sec
56%, time left: 0 sec
62%, time left: 0 sec
68%, time left: 0 sec
75%, time left: 0 sec
81%, time left: 0 sec
87%, time left: 0 sec
93%, time left: 0 sec
                         : Elapsed time for training with 200 events: 0.316 sec         
<HEADER> BDTG                     : [datasetBkg0] : Evaluation of BDTG on training sample (200 events)
0%, time left: unknown
7%, time left: 0 sec
13%, time left: 0 sec
19%, time left: 0 sec
25%, time left: 0 sec
32%, time left: 0 sec
38%, time left: 0 sec
44%, time left: 0 sec
50%, time left: 0 sec
57%, time left: 0 sec
63%, time left: 0 sec
69%, time left: 0 sec
75%, time left: 0 sec
82%, time left: 0 sec
88%, time left: 0 sec
94%, time left: 0 sec
                         : Elapsed time for evaluation of 200 events: 0.02 sec       
                         : Creating xml weight file: datasetBkg0/weights/TMVAMultiBkg0_BDTG.weights.xml
                         : Creating standalone class: datasetBkg0/weights/TMVAMultiBkg0_BDTG.class.C
                         : TMVASignalBackground0.root:/datasetBkg0/Method_BDT/BDTG
<HEADER> Factory                  : Training finished
                         : 
                         : Ranking input variables (method specific)...
<HEADER> BDTG                     : Ranking result (top variable is best ranked)
                         : --------------------------------------
                         : Rank : Variable  : Variable Importance
                         : --------------------------------------
                         :    1 : var1      : 2.632e-01
                         :    2 : var3      : 2.564e-01
                         :    3 : var4      : 2.419e-01
                         :    4 : var2      : 2.385e-01
                         : --------------------------------------
<HEADER> Factory                  : === Destroy and recreate all methods via weight files for testing ===
                         : 
                         : Reading weight file: datasetBkg0/weights/TMVAMultiBkg0_BDTG.weights.xml
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDTG for Classification performance
                         : 
<HEADER> BDTG                     : [datasetBkg0] : Evaluation of BDTG on testing sample (200 events)
0%, time left: unknown
7%, time left: 0 sec
13%, time left: 0 sec
19%, time left: 0 sec
25%, time left: 0 sec
32%, time left: 0 sec
38%, time left: 0 sec
44%, time left: 0 sec
50%, time left: 0 sec
57%, time left: 0 sec
63%, time left: 0 sec
69%, time left: 0 sec
75%, time left: 0 sec
82%, time left: 0 sec
88%, time left: 0 sec
94%, time left: 0 sec
                         : Elapsed time for evaluation of 200 events: 0.0148 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDTG
                         : 
<HEADER> BDTG                     : [datasetBkg0] : Loop over test events and fill histograms with classifier response...
                         : 
<HEADER> TFHandler_BDTG           : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.055642     1.0503   [    -3.1150     2.9998 ]
                         :     var2:   0.028672     1.0729   [    -3.6952     3.1113 ]
                         :     var3:   0.092743     1.1406   [    -3.3587     3.9796 ]
                         :     var4:    0.23382     1.4126   [    -3.7913     4.1179 ]
                         : -----------------------------------------------------------
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : datasetBkg0   BDTG           : 0.947
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : 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   
                         : -------------------------------------------------------------------------------------------------------------------
                         : datasetBkg0          BDTG           : 0.000 (1.000)       0.845 (1.000)      1.000 (1.000)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Dataset:datasetBkg0      : Created tree 'TestTree' with 200 events
                         : 
<HEADER> Dataset:datasetBkg0      : Created tree 'TrainTree' with 200 events
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
create data set info datasetBkg1
<HEADER> DataSetInfo              : [datasetBkg1] : Added class "Signal"
                         : Add Tree TreeS of type Signal with 200 events
<HEADER> DataSetInfo              : [datasetBkg1] : Added class "Background"
                         : Add Tree TreeB1 of type Background with 200 events
<HEADER> Factory                  : Booking method: BDTG
                         : 
                         : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad
                         : --> change to new default NegWeightTreatment=Pray
                         : Building event vectors for type 2 Signal
                         : Dataset[datasetBkg1] :  create input formulas for tree TreeS
                         : Building event vectors for type 2 Background
                         : Dataset[datasetBkg1] :  create input formulas for tree TreeB1
<HEADER> DataSetFactory           : [datasetBkg1] : Number of events in input trees
                         : 
                         : 
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 100
                         : Signal     -- testing events             : 100
                         : Signal     -- training and testing events: 200
                         : Background -- training events            : 100
                         : Background -- testing events             : 100
                         : Background -- training and testing events: 200
                         : 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  +0.303  +0.518  +0.811
                         :    var2:  +0.303  +1.000  +0.747  +0.724
                         :    var3:  +0.518  +0.747  +1.000  +0.825
                         :    var4:  +0.811  +0.724  +0.825  +1.000
                         : ----------------------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  +0.274  +0.597  +0.826
                         :    var2:  +0.274  +1.000  +0.682  +0.644
                         :    var3:  +0.597  +0.682  +1.000  +0.847
                         :    var4:  +0.826  +0.644  +0.847  +1.000
                         : ----------------------------------------
<HEADER> DataSetFactory           : [datasetBkg1] :  
                         : 
<HEADER> Factory                  : Train all methods
<HEADER> Factory                  : [datasetBkg1] : Create Transformation "I" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg1] : Create Transformation "D" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg1] : Create Transformation "P" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg1] : Create Transformation "G" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg1] : Create Transformation "D" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.083014    0.94480   [    -2.7150     2.1743 ]
                         :     var2:    0.37229    0.94120   [    -2.8854     2.5106 ]
                         :     var3:    0.66043    0.97993   [    -2.0033     3.9796 ]
                         :     var4:    0.28995     1.1531   [    -2.6365     3.5074 ]
                         : -----------------------------------------------------------
                         : Preparing the Decorrelation transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   -0.14582     1.0000   [    -3.4135     2.6647 ]
                         :     var2:    0.11415     1.0000   [    -2.8447     2.2622 ]
                         :     var3:    0.75011     1.0000   [    -1.7660     3.9687 ]
                         :     var4:   0.088378     1.0000   [    -2.4420     2.4735 ]
                         : -----------------------------------------------------------
                         : Preparing the Principle Component (PCA) transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:-1.7020e-09     1.6858   [    -4.2730     4.7654 ]
                         :     var2: 1.3679e-09    0.87609   [    -2.5170     2.1666 ]
                         :     var3:-8.7544e-10    0.52362   [    -1.3516     1.1523 ]
                         :     var4: 6.4865e-10    0.43008   [    -1.2095     1.2859 ]
                         : -----------------------------------------------------------
                         : Preparing the Gaussian transformation...
                         : Preparing the Decorrelation transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:    0.18369     1.0000   [    -1.3503     5.8383 ]
                         :     var2:    0.16500     1.0000   [    -2.3714     5.3320 ]
                         :     var3:   0.083789     1.0000   [    -2.3566     6.0195 ]
                         :     var4:   0.067501     1.0000   [    -1.8543     5.1023 ]
                         : -----------------------------------------------------------
                         : Ranking input variables (method unspecific)...
<HEADER> IdTransformation         : Ranking result (top variable is best ranked)
                         : -----------------------------------
                         : Rank : Variable   : Separation
                         : -----------------------------------
                         :    1 : Variable 4 : 3.527e-01
                         :    2 : Variable 1 : 1.869e-01
                         :    3 : Variable 3 : 1.077e-01
                         :    4 : Variable 2 : 9.537e-02
                         : -----------------------------------
<HEADER> Factory                  : Train method: BDTG for Classification
                         : 
<HEADER> BDTG                     : #events: (reweighted) sig: 100 bkg: 100
                         : #events: (unweighted) sig: 100 bkg: 100
                         : Training 1000 Decision Trees ... patience please
0%, time left: unknown
6%, time left: 0 sec
12%, time left: 0 sec
18%, time left: 0 sec
25%, time left: 0 sec
31%, time left: 0 sec
37%, time left: 0 sec
43%, time left: 0 sec
50%, time left: 0 sec
56%, time left: 0 sec
62%, time left: 0 sec
68%, time left: 0 sec
75%, time left: 0 sec
81%, time left: 0 sec
87%, time left: 0 sec
93%, time left: 0 sec
                         : Elapsed time for training with 200 events: 0.284 sec         
<HEADER> BDTG                     : [datasetBkg1] : Evaluation of BDTG on training sample (200 events)
0%, time left: unknown
7%, time left: 0 sec
13%, time left: 0 sec
19%, time left: 0 sec
25%, time left: 0 sec
32%, time left: 0 sec
38%, time left: 0 sec
44%, time left: 0 sec
50%, time left: 0 sec
57%, time left: 0 sec
63%, time left: 0 sec
69%, time left: 0 sec
75%, time left: 0 sec
82%, time left: 0 sec
88%, time left: 0 sec
94%, time left: 0 sec
                         : Elapsed time for evaluation of 200 events: 0.0165 sec       
                         : Creating xml weight file: datasetBkg1/weights/TMVAMultiBkg1_BDTG.weights.xml
                         : Creating standalone class: datasetBkg1/weights/TMVAMultiBkg1_BDTG.class.C
                         : TMVASignalBackground1.root:/datasetBkg1/Method_BDT/BDTG
<HEADER> Factory                  : Training finished
                         : 
                         : Ranking input variables (method specific)...
<HEADER> BDTG                     : Ranking result (top variable is best ranked)
                         : --------------------------------------
                         : Rank : Variable  : Variable Importance
                         : --------------------------------------
                         :    1 : var3      : 2.658e-01
                         :    2 : var2      : 2.585e-01
                         :    3 : var4      : 2.571e-01
                         :    4 : var1      : 2.186e-01
                         : --------------------------------------
<HEADER> Factory                  : === Destroy and recreate all methods via weight files for testing ===
                         : 
                         : Reading weight file: datasetBkg1/weights/TMVAMultiBkg1_BDTG.weights.xml
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDTG for Classification performance
                         : 
<HEADER> BDTG                     : [datasetBkg1] : Evaluation of BDTG on testing sample (200 events)
0%, time left: unknown
7%, time left: 0 sec
13%, time left: 0 sec
19%, time left: 0 sec
25%, time left: 0 sec
32%, time left: 0 sec
38%, time left: 0 sec
44%, time left: 0 sec
50%, time left: 0 sec
57%, time left: 0 sec
63%, time left: 0 sec
69%, time left: 0 sec
75%, time left: 0 sec
82%, time left: 0 sec
88%, time left: 0 sec
94%, time left: 0 sec
                         : Elapsed time for evaluation of 200 events: 0.0197 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDTG
                         : 
<HEADER> BDTG                     : [datasetBkg1] : Loop over test events and fill histograms with classifier response...
                         : 
<HEADER> TFHandler_BDTG           : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.055642     1.0503   [    -3.1150     2.9998 ]
                         :     var2:    0.32867    0.97799   [    -3.0952     3.1113 ]
                         :     var3:    0.59274    0.95223   [    -2.3587     3.9796 ]
                         :     var4:    0.23382     1.4126   [    -3.7913     4.1179 ]
                         : -----------------------------------------------------------
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : datasetBkg1   BDTG           : 0.975
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : 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   
                         : -------------------------------------------------------------------------------------------------------------------
                         : datasetBkg1          BDTG           : 0.000 (1.000)       0.990 (1.000)      1.000 (1.000)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Dataset:datasetBkg1      : Created tree 'TestTree' with 200 events
                         : 
<HEADER> Dataset:datasetBkg1      : Created tree 'TrainTree' with 200 events
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
create data set info datasetBkg2
<HEADER> DataSetInfo              : [datasetBkg2] : Added class "Signal"
                         : Add Tree TreeS of type Signal with 200 events
<HEADER> DataSetInfo              : [datasetBkg2] : Added class "Background"
                         : Add Tree TreeB2 of type Background with 200 events
<HEADER> Factory                  : Booking method: BDTG
                         : 
                         : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad
                         : --> change to new default NegWeightTreatment=Pray
                         : Building event vectors for type 2 Signal
                         : Dataset[datasetBkg2] :  create input formulas for tree TreeS
                         : Building event vectors for type 2 Background
                         : Dataset[datasetBkg2] :  create input formulas for tree TreeB2
<HEADER> DataSetFactory           : [datasetBkg2] : Number of events in input trees
                         : 
                         : 
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 100
                         : Signal     -- testing events             : 100
                         : Signal     -- training and testing events: 200
                         : Background -- training events            : 100
                         : Background -- testing events             : 100
                         : Background -- training and testing events: 200
                         : 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  +0.303  +0.518  +0.811
                         :    var2:  +0.303  +1.000  +0.747  +0.724
                         :    var3:  +0.518  +0.747  +1.000  +0.825
                         :    var4:  +0.811  +0.724  +0.825  +1.000
                         : ----------------------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  -0.614  +0.174  +0.306
                         :    var2:  -0.614  +1.000  -0.190  -0.215
                         :    var3:  +0.174  -0.190  +1.000  +0.009
                         :    var4:  +0.306  -0.215  +0.009  +1.000
                         : ----------------------------------------
<HEADER> DataSetFactory           : [datasetBkg2] :  
                         : 
<HEADER> Factory                  : Train all methods
<HEADER> Factory                  : [datasetBkg2] : Create Transformation "I" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg2] : Create Transformation "D" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg2] : Create Transformation "P" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg2] : Create Transformation "G" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> Factory                  : [datasetBkg2] : Create Transformation "D" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'var1' <---> Output : variable 'var1'
                         : Input : variable 'var2' <---> Output : variable 'var2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:    0.24073    0.88889   [    -2.7150     2.1743 ]
                         :     var2:    0.60716    0.93299   [    -2.8854     2.5106 ]
                         :     var3:    0.26562     1.0821   [    -2.0033     3.3281 ]
                         :     var4:    0.54393     1.1021   [    -1.7460     3.5074 ]
                         : -----------------------------------------------------------
                         : Preparing the Decorrelation transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:    0.15036     1.0000   [    -3.0430     2.1990 ]
                         :     var2:    0.61325     1.0000   [    -2.8964     2.3916 ]
                         :     var3:   0.095300     1.0000   [    -2.0598     2.7739 ]
                         :     var4:    0.41920     1.0000   [    -2.2157     2.5376 ]
                         : -----------------------------------------------------------
                         : Preparing the Principle Component (PCA) transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1: 6.9849e-11     1.4186   [    -3.9626     4.6404 ]
                         :     var2: 6.0303e-10    0.93410   [    -2.0672     2.5744 ]
                         :     var3:-5.5879e-11    0.84463   [    -1.7420     2.3067 ]
                         :     var4:-4.0745e-12    0.66933   [    -1.8960     1.5989 ]
                         : -----------------------------------------------------------
                         : Preparing the Gaussian transformation...
                         : Preparing the Decorrelation transformation...
<HEADER> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:    0.17407     1.0000   [    -1.4936     5.1364 ]
                         :     var2:    0.16814     1.0000   [    -1.5180     4.4057 ]
                         :     var3:    0.11786     1.0000   [    -2.0043     4.6306 ]
                         :     var4:   0.086970     1.0000   [    -2.4719     4.0635 ]
                         : -----------------------------------------------------------
                         : Ranking input variables (method unspecific)...
<HEADER> IdTransformation         : Ranking result (top variable is best ranked)
                         : -----------------------------------
                         : Rank : Variable   : Separation
                         : -----------------------------------
                         :    1 : Variable 2 : 3.966e-01
                         :    2 : Variable 3 : 2.334e-01
                         :    3 : Variable 4 : 2.121e-01
                         :    4 : Variable 1 : 1.602e-01
                         : -----------------------------------
<HEADER> Factory                  : Train method: BDTG for Classification
                         : 
<HEADER> BDTG                     : #events: (reweighted) sig: 100 bkg: 100
                         : #events: (unweighted) sig: 100 bkg: 100
                         : Training 1000 Decision Trees ... patience please
0%, time left: unknown
6%, time left: 0 sec
12%, time left: 0 sec
18%, time left: 0 sec
25%, time left: 0 sec
31%, time left: 0 sec
37%, time left: 0 sec
43%, time left: 0 sec
50%, time left: 0 sec
56%, time left: 0 sec
62%, time left: 0 sec
68%, time left: 0 sec
75%, time left: 0 sec
81%, time left: 0 sec
87%, time left: 0 sec
93%, time left: 0 sec
                         : Elapsed time for training with 200 events: 0.307 sec         
<HEADER> BDTG                     : [datasetBkg2] : Evaluation of BDTG on training sample (200 events)
0%, time left: unknown
7%, time left: 0 sec
13%, time left: 0 sec
19%, time left: 0 sec
25%, time left: 0 sec
32%, time left: 0 sec
38%, time left: 0 sec
44%, time left: 0 sec
50%, time left: 0 sec
57%, time left: 0 sec
63%, time left: 0 sec
69%, time left: 0 sec
75%, time left: 0 sec
82%, time left: 0 sec
88%, time left: 0 sec
94%, time left: 0 sec
                         : Elapsed time for evaluation of 200 events: 0.0198 sec       
                         : Creating xml weight file: datasetBkg2/weights/TMVAMultiBkg2_BDTG.weights.xml
                         : Creating standalone class: datasetBkg2/weights/TMVAMultiBkg2_BDTG.class.C
                         : TMVASignalBackground2.root:/datasetBkg2/Method_BDT/BDTG
<HEADER> Factory                  : Training finished
                         : 
                         : Ranking input variables (method specific)...
<HEADER> BDTG                     : Ranking result (top variable is best ranked)
                         : --------------------------------------
                         : Rank : Variable  : Variable Importance
                         : --------------------------------------
                         :    1 : var1      : 2.839e-01
                         :    2 : var4      : 2.535e-01
                         :    3 : var2      : 2.388e-01
                         :    4 : var3      : 2.238e-01
                         : --------------------------------------
<HEADER> Factory                  : === Destroy and recreate all methods via weight files for testing ===
                         : 
                         : Reading weight file: datasetBkg2/weights/TMVAMultiBkg2_BDTG.weights.xml
<HEADER> Factory                  : Test all methods
<HEADER> Factory                  : Test method: BDTG for Classification performance
                         : 
<HEADER> BDTG                     : [datasetBkg2] : Evaluation of BDTG on testing sample (200 events)
0%, time left: unknown
7%, time left: 0 sec
13%, time left: 0 sec
19%, time left: 0 sec
25%, time left: 0 sec
32%, time left: 0 sec
38%, time left: 0 sec
44%, time left: 0 sec
50%, time left: 0 sec
57%, time left: 0 sec
63%, time left: 0 sec
69%, time left: 0 sec
75%, time left: 0 sec
82%, time left: 0 sec
88%, time left: 0 sec
94%, time left: 0 sec
                         : Elapsed time for evaluation of 200 events: 0.0137 sec       
<HEADER> Factory                  : Evaluate all methods
<HEADER> Factory                  : Evaluate classifier: BDTG
                         : 
<HEADER> BDTG                     : [datasetBkg2] : Loop over test events and fill histograms with classifier response...
                         : 
<HEADER> TFHandler_BDTG           : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:    0.37519    0.89700   [    -2.1665     2.9998 ]
                         :     var2:    0.74853    0.85222   [    -3.0952     3.1113 ]
                         :     var3:    0.32748     1.0975   [    -2.3587     3.9796 ]
                         :     var4:    0.60069     1.2104   [    -2.2913     4.1179 ]
                         : -----------------------------------------------------------
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : datasetBkg2   BDTG           : 0.979
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : 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   
                         : -------------------------------------------------------------------------------------------------------------------
                         : datasetBkg2          BDTG           : 0.769 (0.975)       0.975 (0.979)      0.983 (0.986)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
<HEADER> Dataset:datasetBkg2      : Created tree 'TestTree' with 200 events
                         : 
<HEADER> Dataset:datasetBkg2      : Created tree 'TrainTree' with 200 events
                         : 
<HEADER> Factory                  : Thank you for using TMVA!
                         : For citation information, please visit: http://tmva.sf.net/citeTMVA.html

========================
--- Application & create combined tree
create data set info Default
create data set info Default
create data set info Default
                         : Booking "BDT method" of type "BDT" from datasetBkg0/weights/TMVAMultiBkg0_BDTG.weights.xml.
                         : Reading weight file: datasetBkg0/weights/TMVAMultiBkg0_BDTG.weights.xml
<HEADER> DataSetInfo              : [Default] : Added class "Signal"
<HEADER> DataSetInfo              : [Default] : Added class "Background"
                         : Booked classifier "BDTG" of type: "BDT"
                         : Booking "BDT method" of type "BDT" from datasetBkg1/weights/TMVAMultiBkg1_BDTG.weights.xml.
                         : Reading weight file: datasetBkg1/weights/TMVAMultiBkg1_BDTG.weights.xml
<HEADER> DataSetInfo              : [Default] : Added class "Signal"
<HEADER> DataSetInfo              : [Default] : Added class "Background"
                         : Booked classifier "BDTG" of type: "BDT"
                         : Booking "BDT method" of type "BDT" from datasetBkg2/weights/TMVAMultiBkg2_BDTG.weights.xml.
                         : Reading weight file: datasetBkg2/weights/TMVAMultiBkg2_BDTG.weights.xml
<HEADER> DataSetInfo              : [Default] : Added class "Signal"
<HEADER> DataSetInfo              : [Default] : Added class "Background"
                         : Booked classifier "BDTG" of type: "BDT"
--- Select signal sample
--- Processing: 200 events
--- ... Processing event: 0
--- End of event loop: Real time 0:00:00, CP time 0.030
--- Select background 0 sample
--- Processing: 200 events
--- ... Processing event: 0
--- End of event loop: Real time 0:00:00, CP time 0.040
--- Select background 1 sample
--- Processing: 200 events
--- ... Processing event: 0
--- End of event loop: Real time 0:00:00, CP time 0.030
--- Select background 2 sample
--- Processing: 200 events
--- ... Processing event: 0
--- End of event loop: Real time 0:00:00, CP time 0.050
--- Created root file: "tmva_example_multiple_backgrounds__applied.root" containing the MVA output histograms
==> Application of readers is done! combined tree created


========================
--- maximize significance
Classifier ranges (defined by the user)
 range: -1   1
 range: -1   1
 range: -1   1
<HEADER> FitterBase               : <GeneticFitter> Optimisation, please be patient ... (inaccurate progress timing for GA)
0%, time left: unknown
7%, time left: 47 sec
13%, time left: 30 sec
20%, time left: 49 sec
25%, time left: 39 sec
32%, time left: 31 sec
38%, time left: 29 sec
44%, time left: 24 sec
50%, time left: 26 sec
57%, time left: 21 sec
63%, time left: 17 sec
70%, time left: 13 sec
75%, time left: 11 sec
82%, time left: 7 sec
88%, time left: 5 sec
94%, time left: 2 sec
                         : Elapsed time: 38.8 sec                            

======================
Efficiency : 0.975
Purity     : 0.862832

True positive weights : 195
False positive weights: 31
Signal weights        : 200

  cutValue[0] = -0.960921;
  cutValue[1] = -0.0913659;
  cutValue[2] = -0.995724;