33 #ifndef ROOT_TMVA_MethodSVM
34 #define ROOT_TMVA_MethodSVM
44 #ifndef ROOT_TMVA_MethodBase
47 #ifndef ROOT_TMVA_TMatrixD
48 #ifndef ROOT_TMatrixDfwd
52 #ifndef ROOT_TMVA_TVectorD
62 class SVKernelFunction;
141 #endif // MethodSVM_H
void Train(void)
Train SVM.
void DeclareCompatibilityOptions()
options that are used ONLY for the READER to ensure backward compatibility
Float_t fDoubleSigmaSquared
A ROOT file is a suite of consecutive data records (TKey instances) with a well defined format...
std::vector< TMVA::SVEvent * > * fInputData
void MakeClassSpecific(std::ostream &, const TString &) const
write specific classifier response
void ProcessOptions()
option post processing (if necessary)
#define ClassDef(name, id)
void DeclareOptions()
declare options available for this method
void AddWeightsXMLTo(void *parent) const
write configuration to xml file
void ReadWeightsFromXML(void *wghtnode)
void ReadWeightsFromStream(std::istream &istr)
void Init(void)
default initialisation
SVKernelFunction * fSVKernelFunction
virtual Bool_t HasAnalysisType(Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
SVM can handle classification with 2 classes and regression with one regression-target.
Double_t GetMvaValue(Double_t *err=0, Double_t *errUpper=0)
returns MVA value for given event
std::vector< TMVA::SVEvent * > * fSupportVectors
MethodSVM(const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="", TDirectory *theTargetDir=0)
Describe directory structure in memory.
const Ranking * CreateRanking()
Abstract ClassifierFactory template that handles arbitrary types.
virtual ~MethodSVM(void)
destructor
void WriteWeightsToStream(TFile &fout) const
TODO write IT write training sample (TTree) to file.
virtual void ReadWeightsFromStream(std::istream &)=0
void GetHelpMessage() const
get help message text
const std::vector< Float_t > & GetRegressionValues()