33#ifndef ROOT_TMVA_MethodHMatrix
34#define ROOT_TMVA_MethodHMatrix
#define ClassDef(name, id)
Class that contains all the data information.
Virtual base Class for all MVA method.
virtual void ReadWeightsFromStream(std::istream &)=0
H-Matrix method, which is implemented as a simple comparison of chi-squared estimators for signal and...
virtual ~MethodHMatrix()
destructor
MethodHMatrix(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
standard constructor for the H-Matrix method
void ComputeCovariance(Bool_t, TMatrixD *)
compute covariance matrix
void DeclareOptions()
MethodHMatrix options: none (apart from those implemented in MethodBase)
virtual Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
FDA can handle classification with 2 classes and regression with one regression-target.
Double_t GetChi2(Types::ESBType)
compute chi2-estimator for event according to type (signal/background)
void ProcessOptions()
process user options
void MakeClassSpecific(std::ostream &, const TString &) const
write Fisher-specific classifier response
void Init()
default initialization called by all constructors
void GetHelpMessage() const
get help message text
const Ranking * CreateRanking()
void ReadWeightsFromXML(void *wghtnode)
read weights from XML file
void Train()
computes H-matrices for signal and background samples
Double_t GetMvaValue(Double_t *err=0, Double_t *errUpper=0)
returns the H-matrix signal estimator
void ReadWeightsFromStream(std::istream &istr)
read variable names and min/max NOTE: the latter values are mandatory for the normalisation in the re...
void AddWeightsXMLTo(void *parent) const
create XML description for HMatrix classification
Ranking for variables in method (implementation)
Abstract ClassifierFactory template that handles arbitrary types.