Execution Time8.77s

Test: tutorial-tmva-tmva003_RReader (Passed)
Build: master-x86_64-ubuntu18-clang91-opt (sft-ubuntu-1804-3) on 2020-01-23 01:07:53
Repository revision: fa773cdbdf14a6e74d4700c427c85615076e326c

Test Timing: Passed
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Test output
Processing /mnt/build/night/LABEL/ROOT-ubuntu1804-clangHEAD/SPEC/cxxmod-noimt/V/master/root/tutorials/tmva/tmva003_RReader.C...
create data set info tmva003_BDT
<HEADER> DataSetInfo              : [tmva003_BDT] : Added class "Signal"
                         : Add Tree TreeS of type Signal with 6000 events
<HEADER> DataSetInfo              : [tmva003_BDT] : Added class "Background"
                         : Add Tree TreeB of type Background with 6000 events
                         : Dataset[tmva003_BDT] : Class index : 0  name : Signal
                         : Dataset[tmva003_BDT] : Class index : 1  name : Background
<HEADER> Factory                  : Booking method: BDT
                         : 
                         : Building event vectors for type 2 Signal
                         : Dataset[tmva003_BDT] :  create input formulas for tree TreeS
                         : Building event vectors for type 2 Background
                         : Dataset[tmva003_BDT] :  create input formulas for tree TreeB
<HEADER> DataSetFactory           : [tmva003_BDT] : Number of events in input trees
                         : 
                         : 
                         : Dataset[tmva003_BDT] : Weight renormalisation mode: "EqualNumEvents": renormalises all event classes ...
                         : Dataset[tmva003_BDT] :  such that the effective (weighted) number of events in each class is the same 
                         : Dataset[tmva003_BDT] :  (and equals the number of events (entries) given for class=0 )
                         : Dataset[tmva003_BDT] : ... i.e. such that Sum[i=1..N_j]{w_i} = N_classA, j=classA, classB, ...
                         : Dataset[tmva003_BDT] : ... (note that N_j is the sum of TRAINING events
                         : Dataset[tmva003_BDT] :  ..... Testing events are not renormalised nor included in the renormalisation factor!)
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 3000
                         : Signal     -- testing events             : 3000
                         : Signal     -- training and testing events: 6000
                         : Background -- training events            : 3000
                         : Background -- testing events             : 3000
                         : Background -- training and testing events: 6000
                         : 
<HEADER> DataSetInfo              : Correlation matrix (Signal):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  +0.390  +0.594  +0.819
                         :    var2:  +0.390  +1.000  +0.684  +0.724
                         :    var3:  +0.594  +0.684  +1.000  +0.848
                         :    var4:  +0.819  +0.724  +0.848  +1.000
                         : ----------------------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ----------------------------------------
                         :             var1    var2    var3    var4
                         :    var1:  +1.000  +0.854  +0.917  +0.965
                         :    var2:  +0.854  +1.000  +0.926  +0.934
                         :    var3:  +0.917  +0.926  +1.000  +0.972
                         :    var4:  +0.965  +0.934  +0.972  +1.000
                         : ----------------------------------------
<HEADER> DataSetFactory           : [tmva003_BDT] :  
                         : 
<HEADER> Factory                  : Train all methods
<HEADER> Factory                  : [tmva003_BDT] : 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> TFHandler_Factory        : Variable        Mean        RMS   [        Min        Max ]
                         : -----------------------------------------------------------
                         :     var1:   0.017312     1.6864   [    -5.8991     4.7639 ]
                         :     var2:  0.0068952     1.5665   [    -5.2454     4.6508 ]
                         :     var3:  0.0094455     1.7427   [    -5.3563     4.6430 ]
                         :     var4:    0.16960     2.1719   [    -6.9675     4.9600 ]
                         : -----------------------------------------------------------
                         : Ranking input variables (method unspecific)...
<HEADER> IdTransformation         : Ranking result (top variable is best ranked)
                         : -----------------------------
                         : Rank : Variable  : Separation
                         : -----------------------------
                         :    1 : var4      : 3.564e-01
                         :    2 : var3      : 2.899e-01
                         :    3 : var1      : 2.792e-01
                         :    4 : var2      : 2.260e-01
                         : -----------------------------
<HEADER> Factory                  : Train method: BDT for Classification
                         : 
<HEADER> BDT                      : #events: (reweighted) sig: 3000 bkg: 3000
                         : #events: (unweighted) sig: 3000 bkg: 3000
                         : Training 300 Decision Trees ... patience please
                         : Elapsed time for training with 6000 events: 0.548 sec         
<HEADER> BDT                      : [tmva003_BDT] : Evaluation of BDT on training sample (6000 events)
                         : Elapsed time for evaluation of 6000 events: 0.0782 sec       
                         : Creating xml weight file: tmva003_BDT/weights/tmva003_BDT.weights.xml
                         : Creating standalone class: tmva003_BDT/weights/tmva003_BDT.class.C
                         : TMVA.root:/tmva003_BDT/Method_BDT/BDT
<HEADER> Factory                  : Training finished
                         : 
                         : Ranking input variables (method specific)...
<HEADER> BDT                      : Ranking result (top variable is best ranked)
                         : --------------------------------------
                         : Rank : Variable  : Variable Importance
                         : --------------------------------------
                         :    1 : var4      : 3.940e-01
                         :    2 : var1      : 2.619e-01
                         :    3 : var2      : 1.849e-01
                         :    4 : var3      : 1.592e-01
                         : --------------------------------------
<HEADER> Factory                  : === Destroy and recreate all methods via weight files for testing ===
                         : 
                         : Reading weight file: tmva003_BDT/weights/tmva003_BDT.weights.xml
create data set info Default
Single-event inference: 0.233873

RTensor input for inference on data of multiple events:
{ { -1.14361, -0.822373, -0.495426, -0.629427 } { 2.14344, -0.0189228, 0.26703, 1.26749 } { -0.443913, 0.486827, 0.139535, 0.611483 } }

Prediction performed on multiple events: { 0.173541, -0.0540229, 0.266502 }