31#ifndef ROOT_TMVA_MethodCategory
32#define ROOT_TMVA_MethodCategory
67 const TString& theOption =
"" );
76 void Train(
void )
override;
108 void Init()
override;
unsigned int UInt_t
Unsigned integer 4 bytes (unsigned int).
bool Bool_t
Boolean (0=false, 1=true) (bool).
double Double_t
Double 8 bytes.
long long Long64_t
Portable signed long integer 8 bytes.
#define ClassDefOverride(name, id)
A specialized string object used for TTree selections.
Class that contains all the data information.
Class that contains all the data information.
This is the main MVA steering class.
Interface for all concrete MVA method implementations.
friend class MethodCategory
Class for boosting a TMVA method.
void InitCircularTree(const DataSetInfo &dsi)
initialize the circular tree
void DeclareOptions() override
options for this method
void ReadWeightsFromXML(void *wghtnode) override
read weights of sub-classifiers of MethodCategory from xml weight file
Bool_t PassesCut(const Event *ev, UInt_t methodIdx)
void Train(void) override
train all sub-classifiers
Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t) override
check whether method category has analysis type the method type has to be the same for all sub-method...
MethodCategory(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
standard constructor
const Ranking * CreateRanking() override
no ranking
std::vector< std::vector< UInt_t > > fVarMaps
TMVA::DataSetInfo & CreateCategoryDSI(const TCut &, const TString &, const TString &)
create a DataSetInfo object for a sub-classifier
std::vector< IMethod * > fMethods
DataSetManager * fDataSetManager
std::vector< UInt_t > fCategorySpecIdx
std::vector< TString > fVars
TTree * fCatTree
! needed in conjunction with TTreeFormulas for evaluation category expressions
const std::vector< Float_t > & GetRegressionValues() override
returns the mva value of the right sub-classifier
void Init() override
initialize the method
virtual ~MethodCategory(void)
destructor
void MakeClass(const TString &=TString("")) const override
create reader class for method (classification only at present)
void AddWeightsXMLTo(void *parent) const override
create XML description of Category classifier
void ProcessOptions() override
process user options
std::vector< TTreeFormula * > fCatFormulas
std::vector< TCut > fCategoryCuts
TMVA::IMethod * AddMethod(const TCut &, const TString &theVariables, Types::EMVA theMethod, const TString &theTitle, const TString &theOptions)
adds sub-classifier for a category
void GetHelpMessage() const override
Get help message text.
Double_t GetMvaValue(Double_t *err=nullptr, Double_t *errUpper=nullptr) override
returns the mva value of the right sub-classifier
std::vector< Double_t > GetMvaValues(Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false) override
returns the mva values of the right sub-classifier
const std::vector< Float_t > & GetMulticlassValues() override
returns the mva values of the multi-class right sub-classifier
MethodCompositeBase(const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
Ranking for variables in method (implementation).
The Reader class serves to use the MVAs in a specific analysis context.
A TTree represents a columnar dataset.
create variable transformations