Hello everyone,
I’m trying to train the BDT classifier where the input background is the signal-weighted data using splot technique. After applying the signal-weight to the ntuple some the variables that are used as inputs to BDT have negative content and the TMVAClassification.C is giving error.
: error in matrix diagonalization; printed S and B
: error in matrix diagonalization; printed S and B
: Variable “Mumumass” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “Mumumass” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “Mumumass” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “Bmass” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “Bmass” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “Bmass” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(MumMinIP,MupMinIP)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(MumMinIP,MupMinIP)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(MumMinIP,MupMinIP)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(Mumdcasigbs,Mupdcasigbs)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(Mumdcasigbs,Mupdcasigbs)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(Mumdcasigbs,Mupdcasigbs)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(Mumpt,Muppt)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(Mumpt,Muppt)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
: Variable “TMath::Max(Mumpt,Muppt)” has zero, negative, or NaN RMS^2: -nan ==> set to zero. Please check the variable content
TFHandler_Factory : Variable Mean RMS [ Min Max ]
: -----------------------------------------------------------
: Mumumass: -nan 0.0000 [1.7977e+308-1.7977e+308 ]
: Bmass: -nan 0.0000 [1.7977e+308-1.7977e+308 ]
: IP: -nan 0.0000 [1.7977e+308-1.7977e+308 ]
: DCA: -nan 0.0000 [1.7977e+308-1.7977e+308 ]
: Pt: -nan 0.0000 [1.7977e+308-1.7977e+308 ]
: -----------------------------------------------------------
: -nan -nan -nan -nan -nan -nan
: signal and background histograms have different or invalid dimensions:
***> abort program execution
terminate called after throwing an instance of ‘std::runtime_error’
what(): FATAL error
Please suggest how can I train the BDT using this signal-weighted data.