31#ifndef ROOT_TMVA_MethodFDA
32#define ROOT_TMVA_MethodFDA
78 void Train(
void )
override;
93 void Init(
void )
override;
#define ClassDefOverride(name, id)
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Class that contains all the data information.
Base class for TMVA fitters.
Interface for a fitter 'target'.
Virtual base Class for all MVA method.
void ReadWeightsFromStream(std::istream &) override=0
Function discriminant analysis (FDA).
Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets) override
FDA can handle classification with 2 classes and regression with one regression-target.
TString fFormulaStringT
string with function
const std::vector< Float_t > & GetRegressionValues() override
const Ranking * CreateRanking() override
virtual ~MethodFDA(void)
destructor
Double_t InterpretFormula(const Event *, std::vector< Double_t >::iterator begin, std::vector< Double_t >::iterator end)
formula interpretation
void Train(void) override
FDA training.
void CalculateMulticlassValues(const TMVA::Event *&evt, std::vector< Double_t > ¶meters, std::vector< Float_t > &values)
calculate the values for multiclass
void CheckSetup() override
check may be overridden by derived class (sometimes, eg, fitters are used which can only be implement...
void ReadWeightsFromStream(std::istream &i) override
read back the training results from a file (stream)
Double_t fSumOfWeightsBkg
sum of weights (background)
Int_t fOutputDimensions
number of output values
MethodFDA(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
standard constructor
void ClearAll()
delete and clear all class members
std::vector< Interval * > fParRange
ranges of parameters
void PrintResults(const TString &, std::vector< Double_t > &, const Double_t) const
display fit parameters check maximum length of variable name
Double_t GetMvaValue(Double_t *err=nullptr, Double_t *errUpper=nullptr) override
returns MVA value for given event
Double_t fSumOfWeightsSig
sum of weights (signal)
TString fParRangeStringP
string with ranges of parameters
void MakeClassSpecific(std::ostream &, const TString &) const override
write FDA-specific classifier response
TFormula * fFormula
the discrimination function
std::vector< Double_t > fBestPars
the pars that optimise (minimise) the estimator
void AddWeightsXMLTo(void *parent) const override
create XML description for LD classification and regression (for arbitrary number of output classes/t...
IFitterTarget * fConvergerFitter
intermediate fitter
void ProcessOptions() override
the option string is decoded, for available options see "DeclareOptions"
FitterBase * fFitter
the fitter used in the training
void ReadWeightsFromXML(void *wghtnode) override
read coefficients from xml weight file
Double_t EstimatorFunction(std::vector< Double_t > &) override
compute estimator for given parameter set (to be minimised)
Double_t fSumOfWeights
sum of weights
TString fParRangeStringT
string with ranges of parameters
void DeclareOptions() override
define the options (their key words) that can be set in the option string
const std::vector< Float_t > & GetMulticlassValues() override
TString fFitMethod
estimator optimisation method
void CreateFormula()
translate formula string into TFormula, and parameter string into par ranges
UInt_t fNPars
number of parameters
TString fConverger
fit method uses fConverger as intermediate step to converge into local minimas
TString fFormulaStringP
string with function
void Init(void) override
default initialisation
void GetHelpMessage() const override
get help message text
Ranking for variables in method (implementation)
create variable transformations