31 #ifndef ROOT_TMVA_MethodCategory 32 #define ROOT_TMVA_MethodCategory 64 const TString& theOption =
"" );
std::vector< IMethod * > fMethods
void Init()
initialize the method
TMVA::IMethod * AddMethod(const TCut &, const TString &theVariables, Types::EMVA theMethod, const TString &theTitle, const TString &theOptions)
adds sub-classifier for a category
virtual void MakeClass(const TString &=TString("")) const
create reader class for method (classification only at present)
void InitCircularTree(const DataSetInfo &dsi)
initialize the circular tree
std::vector< TCut > fCategoryCuts
std::vector< UInt_t > fCategorySpecIdx
Ranking for variables in method (implementation)
virtual ~MethodCategory(void)
destructor
std::vector< std::vector< UInt_t > > fVarMaps
#define ClassDef(name, id)
void DeclareOptions()
options for this method
Virtual base class for combining several TMVA method.
Class that contains all the data information.
Class for boosting a TMVA method.
A specialized string object used for TTree selections.
std::vector< TTreeFormula * > fCatFormulas
needed in conjunction with TTreeFormulas for evaluation category expressions
MethodCategory(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
standard constructor
const Ranking * CreateRanking()
no ranking
TMVA::DataSetInfo & CreateCategoryDSI(const TCut &, const TString &, const TString &)
create a DataSetInfo object for a sub-classifier
DataSetManager * fDataSetManager
void Train(void)
train all sub-classifiers
This is the main MVA steering class.
Class for categorizing the phase space.
Class that contains all the data information.
virtual Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t)
check whether method category has analysis type the method type has to be the same for all sub-method...
std::vector< TString > fVars
void GetHelpMessage() const
Get help message text.
Double_t GetMvaValue(Double_t *err=0, Double_t *errUpper=0)
returns the mva value of the right sub-classifier
Interface for all concrete MVA method implementations.
The Reader class serves to use the MVAs in a specific analysis context.
Abstract ClassifierFactory template that handles arbitrary types.
void AddWeightsXMLTo(void *parent) const
create XML description of Category classifier
A TTree object has a header with a name and a title.
void ReadWeightsFromXML(void *wghtnode)
read weights of sub-classifiers of MethodCategory from xml weight file
Bool_t PassesCut(const Event *ev, UInt_t methodIdx)
virtual const std::vector< Float_t > & GetRegressionValues()
returns the mva value of the right sub-classifier
void ProcessOptions()
process user options