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
DataSetInfo : [datasetBkg0] : Added class "Signal" : Add Tree TreeS of type Signal with 200 events
DataSetInfo : [datasetBkg0] : Added class "Background" : Add Tree TreeB0 of type Background with 200 events
Factory : Booking method: BDTG : : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad : --> change to new default NegWeightTreatment=Pray : Rebuilding Dataset datasetBkg0 : 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
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 :
DataSetInfo : Correlation matrix (Signal): : ---------------------------------------- : var1 var2 var3 var4 : var1: +1.000 +0.427 +0.620 +0.834 : var2: +0.427 +1.000 +0.756 +0.779 : var3: +0.620 +0.756 +1.000 +0.854 : var4: +0.834 +0.779 +0.854 +1.000 : ----------------------------------------
DataSetInfo : Correlation matrix (Background): : ---------------------------------------- : var1 var2 var3 var4 : var1: +1.000 +0.404 +0.560 +0.803 : var2: +0.404 +1.000 +0.784 +0.784 : var3: +0.560 +0.784 +1.000 +0.836 : var4: +0.803 +0.784 +0.836 +1.000 : ----------------------------------------
DataSetFactory : [datasetBkg0] : :
Factory : Train all methods
Factory : [datasetBkg0] : Create Transformation "I" with events from all classes. :
: 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'
Factory : [datasetBkg0] : Create Transformation "D" with events from all classes. :
: 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'
Factory : [datasetBkg0] : Create Transformation "P" with events from all classes. :
: 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'
Factory : [datasetBkg0] : Create Transformation "G" with events from all classes. :
: 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'
Factory : [datasetBkg0] : Create Transformation "D" with events from all classes. :
: 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'
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.0088163 1.0188 [ -3.1150 2.2852 ] : var2: 0.043750 1.1258 [ -3.6952 3.1113 ] : var3: 0.091345 1.1793 [ -3.3587 3.9796 ] : var4: 0.20148 1.3300 [ -3.7913 4.1179 ] : ----------------------------------------------------------- : Preparing the Decorrelation transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: -0.12168 1.0000 [ -3.1787 2.4607 ] : var2: -0.061928 1.0000 [ -2.7282 2.4350 ] : var3: -0.014488 1.0000 [ -2.6527 3.2319 ] : var4: 0.28207 1.0000 [ -1.9094 2.3930 ] : ----------------------------------------------------------- : Preparing the Principle Component (PCA) transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 7.9442e-09 2.0999 [ -6.9285 6.2549 ] : var2:-9.4762e-10 0.81623 [ -2.1779 1.8409 ] : var3: 1.3434e-09 0.51228 [ -1.2574 1.2890 ] : var4: 3.1898e-10 0.35594 [ -0.84818 0.98796 ] : ----------------------------------------------------------- : Preparing the Gaussian transformation... : Preparing the Decorrelation transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.18535 1.0000 [ -1.2768 5.4654 ] : var2: 0.14488 1.0000 [ -2.0258 6.0132 ] : var3: 0.11957 1.0000 [ -1.9925 7.5386 ] : var4: 0.044545 1.0000 [ -2.6680 5.5691 ] : ----------------------------------------------------------- : Ranking input variables (method unspecific)...
IdTransformation : Ranking result (top variable is best ranked) : ----------------------------------- : Rank : Variable : Separation : ----------------------------------- : 1 : Variable 4 : 4.271e-01 : 2 : Variable 3 : 3.270e-01 : 3 : Variable 2 : 1.993e-01 : 4 : Variable 1 : 1.440e-01 : -----------------------------------
Factory : Train method: BDTG for Classification :
BDTG : #events: (reweighted) sig: 100 bkg: 100 : #events: (unweighted) sig: 100 bkg: 100 : Training 1000 Decision Trees ... patience please : Elapsed time for training with 200 events: 0.0493 sec
BDTG : [datasetBkg0] : Evaluation of BDTG on training sample (200 events)
BDTG : [datasetBkg0] : Evaluation of BDTG on training sample (200 events) : Elapsed time for evaluation of 200 events: 0.00453 sec : Elapsed time for evaluation of 200 events: 0.00468 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
Factory : Training finished : : Ranking input variables (method specific)...
BDTG : Ranking result (top variable is best ranked) : -------------------------------------- : Rank : Variable : Variable Importance : -------------------------------------- : 1 : var1 : 2.729e-01 : 2 : var2 : 2.642e-01 : 3 : var3 : 2.427e-01 : 4 : var4 : 2.202e-01 : --------------------------------------
Factory : === Destroy and recreate all methods via weight files for testing === : : Reading weight file: datasetBkg0/weights/TMVAMultiBkg0_BDTG.weights.xml
Factory : Test all methods
Factory : Test method: BDTG for Classification performance :
BDTG : [datasetBkg0] : Evaluation of BDTG on testing sample (200 events)
BDTG : [datasetBkg0] : Evaluation of BDTG on testing sample (200 events) : Elapsed time for evaluation of 200 events: 0.00413 sec : Elapsed time for evaluation of 200 events: 0.00492 sec
Factory : Evaluate all methods
Factory : Evaluate classifier: BDTG :
BDTG : [datasetBkg0] : Loop over test events and fill histograms with classifier response... :
TFHandler_BDTG : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.12984 0.97510 [ -2.0823 2.9998 ] : var2: 0.057210 0.86936 [ -1.9349 2.0015 ] : var3: 0.16183 0.98795 [ -2.4774 3.0223 ] : var4: 0.32229 1.2452 [ -2.9030 3.3317 ] : ----------------------------------------------------------- : : Evaluation results ranked by best signal efficiency and purity (area) : ------------------------------------------------------------------------------------------------------------------- : DataSet MVA : Name: Method: ROC-integ : datasetBkg0 BDTG : 0.939 : ------------------------------------------------------------------------------------------------------------------- : : 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 (0.986) 0.825 (1.000) 0.958 (1.000) : ------------------------------------------------------------------------------------------------------------------- :
Dataset:datasetBkg0 : Created tree 'TestTree' with 200 events :
Dataset:datasetBkg0 : Created tree 'TrainTree' with 200 events :
Factory : Thank you for using TMVA! : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
DataSetInfo : [datasetBkg1] : Added class "Signal" : Add Tree TreeS of type Signal with 200 events
DataSetInfo : [datasetBkg1] : Added class "Background" : Add Tree TreeB1 of type Background with 200 events
Factory : Booking method: BDTG : : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad : --> change to new default NegWeightTreatment=Pray : Rebuilding Dataset datasetBkg1 : 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
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 :
DataSetInfo : Correlation matrix (Signal): : ---------------------------------------- : var1 var2 var3 var4 : var1: +1.000 +0.427 +0.620 +0.834 : var2: +0.427 +1.000 +0.756 +0.779 : var3: +0.620 +0.756 +1.000 +0.854 : var4: +0.834 +0.779 +0.854 +1.000 : ----------------------------------------
DataSetInfo : Correlation matrix (Background): : ---------------------------------------- : var1 var2 var3 var4 : var1: +1.000 +0.404 +0.560 +0.803 : var2: +0.404 +1.000 +0.784 +0.784 : var3: +0.560 +0.784 +1.000 +0.836 : var4: +0.803 +0.784 +0.836 +1.000 : ----------------------------------------
DataSetFactory : [datasetBkg1] : :
Factory : Train all methods
Factory : [datasetBkg1] : Create Transformation "I" with events from all classes. :
: 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'
Factory : [datasetBkg1] : Create Transformation "D" with events from all classes. :
: 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'
Factory : [datasetBkg1] : Create Transformation "P" with events from all classes. :
: 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'
Factory : [datasetBkg1] : Create Transformation "G" with events from all classes. :
: 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'
Factory : [datasetBkg1] : Create Transformation "D" with events from all classes. :
: 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'
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.0088163 1.0188 [ -3.1150 2.2852 ] : var2: 0.34375 1.0917 [ -3.0952 3.1113 ] : var3: 0.59134 1.0492 [ -2.3587 3.9796 ] : var4: 0.20148 1.3300 [ -3.7913 4.1179 ] : ----------------------------------------------------------- : Preparing the Decorrelation transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: -0.18819 1.0000 [ -3.1896 2.5009 ] : var2: 0.092430 1.0000 [ -2.5681 2.4906 ] : var3: 0.69993 1.0000 [ -1.8985 3.9795 ] : var4: -0.0086609 1.0000 [ -2.1826 2.3487 ] : ----------------------------------------------------------- : Preparing the Principle Component (PCA) transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 4.8243e-09 1.9581 [ -6.5407 5.8288 ] : var2:-4.0978e-10 0.87524 [ -2.4248 2.2031 ] : var3:-9.3767e-10 0.53717 [ -1.6289 1.2503 ] : var4:-1.2718e-09 0.45934 [ -1.1321 1.1889 ] : ----------------------------------------------------------- : Preparing the Gaussian transformation... : Preparing the Decorrelation transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.17868 1.0000 [ -1.3103 5.4712 ] : var2: 0.11739 1.0000 [ -1.9872 6.1313 ] : var3: 0.13673 1.0000 [ -1.6287 5.9055 ] : var4: 0.068428 1.0000 [ -1.8732 5.5145 ] : ----------------------------------------------------------- : Ranking input variables (method unspecific)...
IdTransformation : Ranking result (top variable is best ranked) : ----------------------------------- : Rank : Variable : Separation : ----------------------------------- : 1 : Variable 4 : 4.271e-01 : 2 : Variable 1 : 1.440e-01 : 3 : Variable 3 : 4.644e-02 : 4 : Variable 2 : 2.725e-02 : -----------------------------------
Factory : Train method: BDTG for Classification :
BDTG : #events: (reweighted) sig: 100 bkg: 100 : #events: (unweighted) sig: 100 bkg: 100 : Training 1000 Decision Trees ... patience please : Elapsed time for training with 200 events: 0.0481 sec
BDTG : [datasetBkg1] : Evaluation of BDTG on training sample (200 events)
BDTG : [datasetBkg1] : Evaluation of BDTG on training sample (200 events) : Elapsed time for evaluation of 200 events: 0.00426 sec : Elapsed time for evaluation of 200 events: 0.0044 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
Factory : Training finished : : Ranking input variables (method specific)...
BDTG : Ranking result (top variable is best ranked) : -------------------------------------- : Rank : Variable : Variable Importance : -------------------------------------- : 1 : var1 : 2.700e-01 : 2 : var3 : 2.528e-01 : 3 : var4 : 2.489e-01 : 4 : var2 : 2.283e-01 : --------------------------------------
Factory : === Destroy and recreate all methods via weight files for testing === : : Reading weight file: datasetBkg1/weights/TMVAMultiBkg1_BDTG.weights.xml
Factory : Test all methods
Factory : Test method: BDTG for Classification performance :
BDTG : [datasetBkg1] : Evaluation of BDTG on testing sample (200 events)
BDTG : [datasetBkg1] : Evaluation of BDTG on testing sample (200 events) : Elapsed time for evaluation of 200 events: 0.00367 sec : Elapsed time for evaluation of 200 events: 0.00441 sec
Factory : Evaluate all methods
Factory : Evaluate classifier: BDTG :
BDTG : [datasetBkg1] : Loop over test events and fill histograms with classifier response... :
TFHandler_BDTG : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.12984 0.97510 [ -2.0823 2.9998 ] : var2: 0.35721 0.80705 [ -1.3349 2.3468 ] : var3: 0.66183 0.87515 [ -1.4774 3.9796 ] : var4: 0.32229 1.2452 [ -2.9030 3.3317 ] : ----------------------------------------------------------- : : Evaluation results ranked by best signal efficiency and purity (area) : ------------------------------------------------------------------------------------------------------------------- : DataSet MVA : Name: Method: ROC-integ : datasetBkg1 BDTG : 0.992 : ------------------------------------------------------------------------------------------------------------------- : : 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) 0.978 (1.000) 1.000 (1.000) : ------------------------------------------------------------------------------------------------------------------- :
Dataset:datasetBkg1 : Created tree 'TestTree' with 200 events :
Dataset:datasetBkg1 : Created tree 'TrainTree' with 200 events :
Factory : Thank you for using TMVA! : For citation information, please visit: http://tmva.sf.net/citeTMVA.html
DataSetInfo : [datasetBkg2] : Added class "Signal" : Add Tree TreeS of type Signal with 200 events
DataSetInfo : [datasetBkg2] : Added class "Background" : Add Tree TreeB2 of type Background with 200 events
Factory : Booking method: BDTG : : the option NegWeightTreatment=InverseBoostNegWeights does not exist for BoostType=Grad : --> change to new default NegWeightTreatment=Pray : Rebuilding Dataset datasetBkg2 : 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
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 :
DataSetInfo : Correlation matrix (Signal): : ---------------------------------------- : var1 var2 var3 var4 : var1: +1.000 +0.427 +0.620 +0.834 : var2: +0.427 +1.000 +0.756 +0.779 : var3: +0.620 +0.756 +1.000 +0.854 : var4: +0.834 +0.779 +0.854 +1.000 : ----------------------------------------
DataSetInfo : Correlation matrix (Background): : ---------------------------------------- : var1 var2 var3 var4 : var1: +1.000 -0.694 -0.018 +0.189 : var2: -0.694 +1.000 +0.048 -0.106 : var3: -0.018 +0.048 +1.000 -0.033 : var4: +0.189 -0.106 -0.033 +1.000 : ----------------------------------------
DataSetFactory : [datasetBkg2] : :
Factory : Train all methods
Factory : [datasetBkg2] : Create Transformation "I" with events from all classes. :
: 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'
Factory : [datasetBkg2] : Create Transformation "D" with events from all classes. :
: 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'
Factory : [datasetBkg2] : Create Transformation "P" with events from all classes. :
: 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'
Factory : [datasetBkg2] : Create Transformation "G" with events from all classes. :
: 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'
Factory : [datasetBkg2] : Create Transformation "D" with events from all classes. :
: 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'
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.28578 0.91179 [ -2.7150 2.2852 ] : var2: 0.67483 0.96936 [ -3.0952 3.1113 ] : var3: 0.31482 1.1483 [ -2.3587 3.9796 ] : var4: 0.47104 1.1963 [ -2.2913 4.1179 ] : ----------------------------------------------------------- : Preparing the Decorrelation transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.21314 1.0000 [ -2.9018 2.2127 ] : var2: 0.65434 1.0000 [ -2.8620 2.8045 ] : var3: 0.097560 1.0000 [ -2.1290 2.6029 ] : var4: 0.28364 1.0000 [ -2.2148 2.5819 ] : ----------------------------------------------------------- : Preparing the Principle Component (PCA) transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1:-1.8283e-09 1.5535 [ -5.3869 5.6955 ] : var2: 8.3819e-10 0.94853 [ -2.3039 2.7397 ] : var3:-2.2631e-09 0.82510 [ -2.0402 1.8198 ] : var4: 1.3062e-09 0.72605 [ -1.7460 1.7342 ] : ----------------------------------------------------------- : Preparing the Gaussian transformation... : Preparing the Decorrelation transformation...
TFHandler_Factory : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.17765 1.0000 [ -1.4239 4.6740 ] : var2: 0.15482 1.0000 [ -1.4140 5.3487 ] : var3: 0.12377 1.0000 [ -1.8596 5.4085 ] : var4: 0.098067 1.0000 [ -2.1757 4.5835 ] : ----------------------------------------------------------- : Ranking input variables (method unspecific)...
IdTransformation : Ranking result (top variable is best ranked) : ----------------------------------- : Rank : Variable : Separation : ----------------------------------- : 1 : Variable 2 : 4.041e-01 : 2 : Variable 4 : 2.872e-01 : 3 : Variable 3 : 2.701e-01 : 4 : Variable 1 : 1.551e-01 : -----------------------------------
Factory : Train method: BDTG for Classification :
BDTG : #events: (reweighted) sig: 100 bkg: 100 : #events: (unweighted) sig: 100 bkg: 100 : Training 1000 Decision Trees ... patience please : Elapsed time for training with 200 events: 0.0469 sec
BDTG : [datasetBkg2] : Evaluation of BDTG on training sample (200 events)
BDTG : [datasetBkg2] : Evaluation of BDTG on training sample (200 events) : Elapsed time for evaluation of 200 events: 0.00467 sec : Elapsed time for evaluation of 200 events: 0.00483 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
Factory : Training finished : : Ranking input variables (method specific)...
BDTG : Ranking result (top variable is best ranked) : -------------------------------------- : Rank : Variable : Variable Importance : -------------------------------------- : 1 : var4 : 3.129e-01 : 2 : var1 : 2.426e-01 : 3 : var2 : 2.242e-01 : 4 : var3 : 2.203e-01 : --------------------------------------
Factory : === Destroy and recreate all methods via weight files for testing === : : Reading weight file: datasetBkg2/weights/TMVAMultiBkg2_BDTG.weights.xml
Factory : Test all methods
Factory : Test method: BDTG for Classification performance :
BDTG : [datasetBkg2] : Evaluation of BDTG on testing sample (200 events)
BDTG : [datasetBkg2] : Evaluation of BDTG on testing sample (200 events) : Elapsed time for evaluation of 200 events: 0.00408 sec : Elapsed time for evaluation of 200 events: 0.00492 sec
Factory : Evaluate all methods
Factory : Evaluate classifier: BDTG :
BDTG : [datasetBkg2] : Loop over test events and fill histograms with classifier response... :
TFHandler_BDTG : Variable Mean RMS [ Min Max ] : ----------------------------------------------------------- : var1: 0.33014 0.87831 [ -1.8821 2.9998 ] : var2: 0.68086 0.81675 [ -1.2800 2.0015 ] : var3: 0.27828 1.0286 [ -1.8691 3.0223 ] : var4: 0.67359 1.1090 [ -1.7755 3.3317 ] : ----------------------------------------------------------- : : Evaluation results ranked by best signal efficiency and purity (area) : ------------------------------------------------------------------------------------------------------------------- : DataSet MVA : Name: Method: ROC-integ : datasetBkg2 BDTG : 0.944 : ------------------------------------------------------------------------------------------------------------------- : : 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 : 0.000 (0.975) 0.000 (0.979) 0.978 (0.986) : ------------------------------------------------------------------------------------------------------------------- :
Dataset:datasetBkg2 : Created tree 'TestTree' with 200 events :
Dataset:datasetBkg2 : Created tree 'TrainTree' with 200 events :
Factory : Thank you for using TMVA! : For citation information, please visit: http://tmva.sf.net/citeTMVA.html ======================== --- Application & create combined tree : Booking "BDT method" of type "BDT" from datasetBkg0/weights/TMVAMultiBkg0_BDTG.weights.xml. : Reading weight file: datasetBkg0/weights/TMVAMultiBkg0_BDTG.weights.xml
DataSetInfo : [Default] : Added class "Signal"
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
DataSetInfo : [Default] : Added class "Signal"
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
DataSetInfo : [Default] : Added class "Signal"
DataSetInfo : [Default] : Added class "Background" : Booked classifier "BDTG" of type: "BDT" --- Select signal sample : Rebuilding Dataset Default : Rebuilding Dataset Default : Rebuilding Dataset Default --- End of event loop: Real time 0:00:00, CP time 0.010 --- Select background 0 sample --- End of event loop: Real time 0:00:00, CP time 0.020 --- Select background 1 sample --- End of event loop: Real time 0:00:00, CP time 0.010 --- Select background 2 sample --- End of event loop: Real time 0:00:00, CP time 0.020 --- 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
FitterBase : Optimisation, please be patient ... (inaccurate progress timing for GA) : Elapsed time: 3.86 sec ====================== Efficiency : 0.93 Purity : 0.881517 True positive weights : 186 False positive weights: 25 Signal weights : 200 cutValue[0] = -0.886275; cutValue[1] = 0.937167; cutValue[2] = 0.79271;