5#ifndef ROOT_TMVA_VariableImportance
6#define ROOT_TMVA_VariableImportance
#define ClassDef(name, id)
1-D histogram with a float per channel (see TH1 documentation)}
Abstract base class for all high level ml algorithms, you can book ml methods like BDT,...
class to storage options for the differents methods
~VariableImportanceResult()
OptionMap & GetImportanceValues()
std::shared_ptr< TH1F > fImportanceHist
TCanvas * Draw(const TString name="VariableImportance") const
TH1F * GetImportanceHist()
VariableImportanceResult()
OptionMap fImportanceValues
std::unique_ptr< Factory > fClassifier
void EvaluateImportanceShort()
const VariableImportanceResult & GetResults() const
virtual void Evaluate()
Virtual method to be implemented with your algorithm.
void EvaluateImportanceRandom(UInt_t nseeds)
VariableImportanceResult fResults
VariableImportance(DataLoader *loader)
void SetType(VIType type)
TH1F * GetImportance(const UInt_t nbits, std::vector< Float_t > &importances, std::vector< TString > &varNames)
void EvaluateImportanceAll()
create variable transformations