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 BDTG
                         : 
                         : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad
                         : --> change to new default NegWeightTreatment=Pray
                         : Rebuilding Dataset dataset
                         : 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  -0.007  +0.754  +0.922
                         :  myvar2:  -0.007  +1.000  -0.065  +0.083
                         :    var3:  +0.754  -0.065  +1.000  +0.836
                         :    var4:  +0.922  +0.083  +0.836  +1.000
                         : ----------------------------------------
<HEADER> DataSetInfo              : Correlation matrix (Background):
                         : ----------------------------------------
                         :           myvar1  myvar2    var3    var4
                         :  myvar1:  +1.000  -0.073  +0.784  +0.925
                         :  myvar2:  -0.073  +1.000  -0.142  +0.019
                         :    var3:  +0.784  -0.142  +1.000  +0.844
                         :    var4:  +0.925  +0.019  +0.844  +1.000
                         : ----------------------------------------
<HEADER> DataSetFactory           : [dataset] :  
                         : 
<HEADER>                          : Loading booked method: SVM SVM
                         : 
<HEADER> SVM                      : [dataset] : Create Transformation "Norm" with events from all classes.
                         : 
<HEADER>                          : Transformation, Variable selection : 
                         : Input : variable 'myvar1' <---> Output : variable 'myvar1'
                         : Input : variable 'myvar2' <---> Output : variable 'myvar2'
                         : Input : variable 'var3' <---> Output : variable 'var3'
                         : Input : variable 'var4' <---> Output : variable 'var4'
<HEADER>                          : Loading booked method: BDT BDTB
                         : 
<HEADER>                          : Loading booked method: Cuts Cuts
                         : 
                         : Use optimization method: "Monte Carlo"
                         : Use efficiency computation method: "Event Selection"
                         : Use "FSmart" cuts for variable: 'myvar1'
                         : Use "FSmart" cuts for variable: 'myvar2'
                         : Use "FSmart" cuts for variable: 'var3'
                         : Use "FSmart" cuts for variable: 'var4'
                         : --------------------------------------------------- :
                         : DataSet              MVA                            :
                         : Name:                Method/Title:    ROC-integ     :
                         : --------------------------------------------------- :
                         : dataset              SVM/SVM          0.901         :
                         : dataset              Cuts/Cuts        0.791         :
                         : dataset              BDT/BDTB         0.854         :
                         : dataset              BDT/BDTG         0.886         :
                         : --------------------------------------------------- :
                         : -----------------------------------------------------
<HEADER>                          : Evaluation done.
                         : 
                         : Jobs = 4 Real Time = 1.857498 
                         : -----------------------------------------------------
                         : Evaluation done.