Definition at line 49 of file OptimizeConfigParameters.h.
#include <TMVA/OptimizeConfigParameters.h>
◆ OptimizeConfigParameters()
◆ ~OptimizeConfigParameters()
TMVA::OptimizeConfigParameters::~OptimizeConfigParameters |
( |
| ) |
|
|
virtual |
◆ EstimatorFunction()
Double_t TMVA::OptimizeConfigParameters::EstimatorFunction |
( |
std::vector< Double_t > & |
pars | ) |
|
|
privatevirtual |
◆ GetBkgEffAtSigEff()
Double_t TMVA::OptimizeConfigParameters::GetBkgEffAtSigEff |
( |
Double_t |
sigEff = 0.5 | ) |
|
|
private |
◆ GetBkgRejAtSigEff()
Double_t TMVA::OptimizeConfigParameters::GetBkgRejAtSigEff |
( |
Double_t |
sigEff = 0.5 | ) |
|
|
private |
◆ GetFOM()
Double_t TMVA::OptimizeConfigParameters::GetFOM |
( |
| ) |
|
|
private |
◆ GetMethod()
MethodBase * TMVA::OptimizeConfigParameters::GetMethod |
( |
| ) |
|
|
inlineprivate |
◆ GetMVADists()
void TMVA::OptimizeConfigParameters::GetMVADists |
( |
| ) |
|
|
private |
◆ GetROCIntegral()
Double_t TMVA::OptimizeConfigParameters::GetROCIntegral |
( |
| ) |
|
|
private |
calculate the area (integral) under the ROC curve as a overall quality measure of the classification
making pdfs out of the MVA-output distributions doesn't work reliably for cases where the MVA-output isn't a smooth distribution. this happens "frequently" in BDTs for example when the number of trees is small resulting in only some discrete possible MVA output values. (I still leave the code here, but use this with care!!! The default however is to use the distributions!!!
Definition at line 458 of file OptimizeConfigParameters.cxx.
◆ GetScanIndices()
std::vector< int > TMVA::OptimizeConfigParameters::GetScanIndices |
( |
int |
val, |
|
|
std::vector< int > |
base |
|
) |
| |
|
private |
◆ GetSeparation()
Double_t TMVA::OptimizeConfigParameters::GetSeparation |
( |
| ) |
|
|
private |
◆ GetSigEffAtBkgEff()
Double_t TMVA::OptimizeConfigParameters::GetSigEffAtBkgEff |
( |
Double_t |
bkgEff = 0.1 | ) |
|
|
private |
◆ Log()
MsgLogger & TMVA::OptimizeConfigParameters::Log |
( |
| ) |
const |
|
inlineprivate |
◆ optimize()
◆ optimizeFit()
void TMVA::OptimizeConfigParameters::optimizeFit |
( |
| ) |
|
|
private |
◆ optimizeScan()
void TMVA::OptimizeConfigParameters::optimizeScan |
( |
| ) |
|
|
private |
do the actual optimization using a simple scan method, i.e.
calculate the FOM for different tuning paraemters and remember which one is gave the best FOM
Definition at line 164 of file OptimizeConfigParameters.cxx.
◆ fAlreadyTrainedParCombination
std::map< std::vector<Double_t> , Double_t> TMVA::OptimizeConfigParameters::fAlreadyTrainedParCombination |
|
private |
◆ fFOMType
TString TMVA::OptimizeConfigParameters::fFOMType |
|
private |
◆ fFOMvsIter
std::vector<Float_t> TMVA::OptimizeConfigParameters::fFOMvsIter |
|
private |
◆ fLogger
MsgLogger* TMVA::OptimizeConfigParameters::fLogger |
|
mutableprivate |
◆ fMethod
MethodBase* const TMVA::OptimizeConfigParameters::fMethod |
|
private |
◆ fMvaBkg
TH1D* TMVA::OptimizeConfigParameters::fMvaBkg |
|
private |
◆ fMvaBkgFineBin
TH1D* TMVA::OptimizeConfigParameters::fMvaBkgFineBin |
|
private |
◆ fMvaSig
TH1D* TMVA::OptimizeConfigParameters::fMvaSig |
|
private |
◆ fMvaSigFineBin
TH1D* TMVA::OptimizeConfigParameters::fMvaSigFineBin |
|
private |
◆ fNotDoneYet
Bool_t TMVA::OptimizeConfigParameters::fNotDoneYet |
|
private |
◆ fOptimizationFitType
TString TMVA::OptimizeConfigParameters::fOptimizationFitType |
|
private |
◆ fTunedParameters
std::map<TString,Double_t> TMVA::OptimizeConfigParameters::fTunedParameters |
|
private |
◆ fTuneParameters
◆ TestOptimizeConfigParameters
friend TMVA::OptimizeConfigParameters::TestOptimizeConfigParameters |
The documentation for this class was generated from the following files: