library: libTMVA
#include "MethodBayesClassifier.h"

TMVA::MethodBayesClassifier

class description - header file - source file
viewCVS header - viewCVS source

class TMVA::MethodBayesClassifier: public TMVA::MethodBase

Inheritance Inherited Members Includes Libraries
Class Charts

Function Members (Methods)

Display options:
Show inherited
Show non-public
public:
virtual~MethodBayesClassifier()
voidTObject::AbstractMethod(const char* method) const
virtual voidTObject::AppendPad(Option_t* option = "")
virtual voidTObject::Browse(TBrowser* b)
static TClass*Class()
virtual const char*TObject::ClassName() const
virtual voidTObject::Clear(Option_t* = "")
virtual TObject*TObject::Clone(const char* newname = "") const
virtual Int_tTObject::Compare(const TObject* obj) const
virtual voidTObject::Copy(TObject& object) const
virtual const TMVA::Ranking*CreateRanking()
TMVA::DataSet&TMVA::MethodBase::Data() const
virtual voidTObject::Delete(Option_t* option = "")
virtual Int_tTObject::DistancetoPrimitive(Int_t px, Int_t py)
virtual voidTObject::Draw(Option_t* option = "")
virtual voidTObject::DrawClass() const
virtual TObject*TObject::DrawClone(Option_t* option = "") const
virtual voidTObject::Dump() const
virtual voidTObject::Error(const char* method, const char* msgfmt) const
virtual voidTObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual voidTObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual voidTObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual voidTObject::Fatal(const char* method, const char* msgfmt) const
virtual TObject*TObject::FindObject(const char* name) const
virtual TObject*TObject::FindObject(const TObject* obj) const
virtual Option_t*TObject::GetDrawOption() const
static Long_tTObject::GetDtorOnly()
Double_tTMVA::MethodBase::GetEffForRoot(Double_t)
virtual Double_tTMVA::MethodBase::GetEfficiency(TString, TTree*)
Double_tTMVA::MethodBase::GetEventVal(Int_t ivar) const
Double_tTMVA::MethodBase::GetEventValNormalized(Int_t ivar) const
Double_tTMVA::MethodBase::GetEventWeight() const
virtual const char*TObject::GetIconName() const
const TString&TMVA::MethodBase::GetInputExp(int i) const
const TString&TMVA::MethodBase::GetInputVar(int i) const
virtual const TString&TMVA::MethodBase::GetJobName() const
virtual const TString&TMVA::MethodBase::GetMethodName() const
virtual const TString&TMVA::MethodBase::GetMethodTitle() const
virtual const TMVA::Types::EMVATMVA::MethodBase::GetMethodType() const
virtual Double_tTMVA::MethodBase::GetmuTransform(TTree*)
virtual Double_tGetMvaValue()
virtual const char*TMVA::MethodBase::GetName() const
Int_tTMVA::MethodBase::GetNvar() const
virtual char*TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_tTObject::GetObjectStat()
virtual Double_tTMVA::MethodBase::GetOptimalSignificance(Double_t SignalEvents, Double_t BackgroundEvents, Double_t& optimal_significance_value) const
virtual Option_t*TObject::GetOption() const
TStringTMVA::MethodBase::GetOptions() const
virtual TMVA::Types::EPreprocessingMethodTMVA::MethodBase::GetPreprocessingMethod() const
virtual Double_tTMVA::MethodBase::GetSeparation()
virtual Double_tTMVA::MethodBase::GetSignificance()
TTree*TMVA::MethodBase::GetTestTree() const
static TMVA::MethodBase*TMVA::MethodBase::GetThisBase()
virtual const char*TObject::GetTitle() const
virtual Double_tTMVA::MethodBase::GetTrainingEfficiency(TString)
TTree*TMVA::MethodBase::GetTrainingTree() const
virtual UInt_tTObject::GetUniqueID() const
virtual TStringTMVA::MethodBase::GetWeightFileDir() const
virtual TStringTMVA::MethodBase::GetWeightFileExtension() const
TStringTMVA::MethodBase::GetWeightFileName() const
TMVA::MethodBase::EWeightFileTypeTMVA::MethodBase::GetWeightFileType() const
Double_tTMVA::MethodBase::GetXmax(Int_t ivar, TMVA::Types::EPreprocessingMethod corr = Types::kNone) const
Double_tTMVA::MethodBase::GetXmax(const TString& var, TMVA::Types::EPreprocessingMethod corr = Types::kNone) const
Double_tTMVA::MethodBase::GetXmin(Int_t ivar, TMVA::Types::EPreprocessingMethod corr = Types::kNone) const
Double_tTMVA::MethodBase::GetXmin(const TString& var, TMVA::Types::EPreprocessingMethod corr = Types::kNone) const
virtual Bool_tTObject::HandleTimer(TTimer* timer)
virtual ULong_tTObject::Hash() const
Bool_tTMVA::MethodBase::HasTrainingTree() const
static Double_tTMVA::MethodBase::IGetEffForRoot(Double_t)
virtual voidTObject::Info(const char* method, const char* msgfmt) const
virtual Bool_tTObject::InheritsFrom(const char* classname) const
virtual Bool_tTObject::InheritsFrom(const TClass* cl) const
voidInitBayesClassifier()
virtual voidTObject::Inspect() const
voidTObject::InvertBit(UInt_t f)
virtual TClass*IsA() const
virtual Bool_tTObject::IsEqual(const TObject* obj) const
virtual Bool_tTObject::IsFolder() const
virtual Bool_tTMVA::MethodBase::IsOK() const
Bool_tTObject::IsOnHeap() const
virtual Bool_tTMVA::MethodBase::IsSignalLike()
virtual Bool_tTObject::IsSortable() const
Bool_tTObject::IsZombie() const
virtual voidTObject::ls(Option_t* option = "") const
voidTObject::MayNotUse(const char* method) const
TMVA::MethodBayesClassifierMethodBayesClassifier(TMVA::DataSet& theData, TString theWeightFile, TDirectory* theTargetDir = NULL)
TMVA::MethodBayesClassifierMethodBayesClassifier(TString jobName, TString methodTitle, TMVA::DataSet& theData, TString theOption = , TDirectory* theTargetDir = 0)
Double_tTMVA::MethodBase::Norm(Int_t ivar, Double_t x) const
Double_tTMVA::MethodBase::Norm(TString var, Double_t x) const
virtual Bool_tTObject::Notify()
static voidTObject::operator delete(void* ptr)
static voidTObject::operator delete(void* ptr, void* vp)
static voidTObject::operator delete[](void* ptr)
static voidTObject::operator delete[](void* ptr, void* vp)
void*TObject::operator new(size_t sz)
void*TObject::operator new(size_t sz, void* vp)
void*TObject::operator new[](size_t sz)
void*TObject::operator new[](size_t sz, void* vp)
TMVA::IMethod&TMVA::IMethod::operator=(const TMVA::IMethod&)
virtual voidTObject::Paint(Option_t* option = "")
virtual voidTObject::Pop()
virtual voidTMVA::MethodBase::PrepareEvaluationTree(TTree* theTestTree)
virtual voidTObject::Print(Option_t* option = "") const
virtual Int_tTObject::Read(const char* name)
virtual voidTMVA::MethodBase::ReadStateFromFile()
virtual voidTMVA::MethodBase::ReadStateFromStream(istream& i)
virtual Bool_tTMVA::MethodBase::ReadTestEvent(UInt_t ievt, TMVA::Types::ESBType type = Types::kMaxSBType)
Bool_tTMVA::MethodBase::ReadTrainingEvent(UInt_t ievt, TMVA::Types::ESBType type = Types::kMaxSBType)
virtual voidReadWeightsFromStream(istream& istr)
virtual voidTObject::RecursiveRemove(TObject* obj)
voidTObject::ResetBit(UInt_t f)
virtual voidTObject::SaveAs(const char* filename = "", Option_t* option = "") const
virtual voidTObject::SavePrimitive(ostream& out, Option_t* option = "")
voidTObject::SetBit(UInt_t f)
voidTObject::SetBit(UInt_t f, Bool_t set)
virtual voidTObject::SetDrawOption(Option_t* option = "")
static voidTObject::SetDtorOnly(void* obj)
virtual voidTMVA::MethodBase::SetJobName(TString jobName)
voidTMVA::MethodBase::SetMethodName(TString methodName)
voidTMVA::MethodBase::SetMethodTitle(TString methodTitle)
voidTMVA::MethodBase::SetMethodType(TMVA::Types::EMVA methodType)
voidTMVA::MethodBase::SetNvar(Int_t n)
static voidTObject::SetObjectStat(Bool_t stat)
voidTMVA::MethodBase::SetPreprocessingMethod(TMVA::Types::EPreprocessingMethod m)
virtual voidTObject::SetUniqueID(UInt_t uid)
voidTMVA::MethodBase::SetVerbose(Bool_t v = kTRUE)
virtual voidTMVA::MethodBase::SetWeightFileDir(TString fileDir)
virtual voidTMVA::MethodBase::SetWeightFileExtension(TString fileExtension)
voidTMVA::MethodBase::SetWeightFileName(TString)
voidTMVA::MethodBase::SetWeightFileType(TMVA::MethodBase::EWeightFileType w)
voidTMVA::MethodBase::SetXmax(Int_t ivar, Double_t x, TMVA::Types::EPreprocessingMethod corr = Types::kNone)
voidTMVA::MethodBase::SetXmax(const TString& var, Double_t x, TMVA::Types::EPreprocessingMethod corr = Types::kNone)
voidTMVA::MethodBase::SetXmin(Int_t ivar, Double_t x, TMVA::Types::EPreprocessingMethod corr = Types::kNone)
voidTMVA::MethodBase::SetXmin(const TString& var, Double_t x, TMVA::Types::EPreprocessingMethod corr = Types::kNone)
virtual voidShowMembers(TMemberInspector& insp, char* parent)
virtual voidStreamer(TBuffer& b)
voidStreamerNVirtual(TBuffer& b)
virtual voidTObject::SysError(const char* method, const char* msgfmt) const
virtual voidTMVA::MethodBase::Test(TTree* theTestTree = 0)
Bool_tTObject::TestBit(UInt_t f) const
Int_tTObject::TestBits(UInt_t f) const
virtual voidTMVA::MethodBase::TestInit(TTree* theTestTree = 0)
virtual voidTrain()
voidTMVA::MethodBase::TrainMethod()
virtual voidTObject::UseCurrentStyle()
Bool_tTMVA::MethodBase::Verbose() const
virtual voidTObject::Warning(const char* method, const char* msgfmt) const
virtual Int_tTObject::Write(const char* name = "0", Int_t option = 0, Int_t bufsize = 0)
virtual Int_tTObject::Write(const char* name = "0", Int_t option = 0, Int_t bufsize = 0) const
virtual voidTMVA::MethodBase::WriteEvaluationHistosToFile(TDirectory* targetDir)
virtual voidTMVA::MethodBase::WriteMonitoringHistosToFile() const
voidTMVA::MethodBase::WriteStateToFile() const
virtual voidTMVA::MethodBase::WriteStateToStream(ostream& o) const
virtual voidWriteWeightsToStream(ostream& o) const
protected:
TDirectory*TMVA::MethodBase::BaseDir() const
Bool_tTMVA::MethodBase::CheckSanity(TTree* theTree = 0)
virtual voidTObject::DoError(int level, const char* location, const char* fmt, va_list va) const
voidTMVA::MethodBase::EnableLooseOptions(Bool_t b = kTRUE)
TMVA::MethodBase::ECutOrientationTMVA::MethodBase::GetCutOrientation() const
TMVA::Types::ESBTypeTMVA::MethodBase::GetPreprocessingType() const
Double_tTMVA::MethodBase::GetSignalReferenceCut() const
const TString&TMVA::MethodBase::GetTestvarName() const
const TString&TMVA::MethodBase::GetTestvarPrefix() const
const TList&TMVA::MethodBase::ListOfOptions() const
TDirectory*TMVA::MethodBase::LocalTDir() const
voidTObject::MakeZombie()
voidTMVA::MethodBase::ParseOptions(Bool_t verbose = kTRUE)
voidTMVA::MethodBase::PrintOptions() const
voidTMVA::MethodBase::ReadOptionsFromStream(istream& istr)
voidTMVA::MethodBase::ResetThisBase()
voidTMVA::MethodBase::SetPreprocessingType(TMVA::Types::ESBType t)
voidTMVA::MethodBase::SetSignalReferenceCut(Double_t cut)
voidTMVA::MethodBase::SetTestvarName()
voidTMVA::MethodBase::SetTestvarName(TString v)
voidTMVA::MethodBase::SetTestvarPrefix(TString prefix)
voidTMVA::MethodBase::Statistics(TMVA::Types::ETreeType treeType, const TString& theVarName, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&, Bool_t norm = kFALSE)
voidTMVA::MethodBase::WriteOptionsToStream(ostream& o) const
private:
virtual voidDeclareOptions()
virtual voidProcessOptions()

Data Members

public:
enum TMVA::MethodBase::EWeightFileType { kROOT
kTEXT
};
enum TMVA::MethodBase::ECutOrientation { kNegative
kPositive
};
enum TObject::EStatusBits { kCanDelete
kMustCleanup
kObjInCanvas
kIsReferenced
kHasUUID
kCannotPick
kNoContextMenu
kInvalidObject
};
enum TObject::[unnamed] { kIsOnHeap
kNotDeleted
kZombie
kBitMask
kSingleKey
kOverwrite
kWriteDelete
};
protected:
TMVA::Ranking*TMVA::MethodBase::fRankingranking
vector<TString>*TMVA::MethodBase::fInputVarsvector of input variables used in MVA
Bool_tTMVA::MethodBase::fIsOKstatus of sanity checks
TH1*TMVA::MethodBase::fHistS_plotbinMVA plots used for graphics representation (signal)
TH1*TMVA::MethodBase::fHistB_plotbinMVA plots used for graphics representation (background)
TH1*TMVA::MethodBase::fHistS_highbinMVA plots used for efficiency calculations (signal)
TH1*TMVA::MethodBase::fHistB_highbinMVA plots used for efficiency calculations (background)
TH1*TMVA::MethodBase::fEffSefficiency plot (signal)
TH1*TMVA::MethodBase::fEffBefficiency plot (background)
TH1*TMVA::MethodBase::fEffBvsSbackground efficiency versus signal efficiency
TH1*TMVA::MethodBase::fRejBvsSbackground rejection (=1-eff.) versus signal efficiency
TH1*TMVA::MethodBase::fHistBhatSworking histograms needed for mu-transform (signal)
TH1*TMVA::MethodBase::fHistBhatBworking histograms needed for mu-transform (background)
TH1*TMVA::MethodBase::fHistMuSmu-transform (signal)
TH1*TMVA::MethodBase::fHistMuBmu-transform (background)
TH1*TMVA::MethodBase::fTrainEffSTraining efficiency plot (signal)
TH1*TMVA::MethodBase::fTrainEffBTraining efficiency plot (background)
TH1*TMVA::MethodBase::fTrainEffBvsSTraining background efficiency versus signal efficiency
TH1*TMVA::MethodBase::fTrainRejBvsSTraining background rejection (=1-eff.) versus signal efficiency
Double_tTMVA::MethodBase::fX
Double_tTMVA::MethodBase::fMode
TGraph*TMVA::MethodBase::fGraphSgraphs used for splines for efficiency (signal)
TGraph*TMVA::MethodBase::fGraphBgraphs used for splines for efficiency (background)
TGraph*TMVA::MethodBase::fGrapheffBvsSgraphs used for splines for signal eff. versus background eff.
TMVA::PDF*TMVA::MethodBase::fSplSPDFs of MVA distribution (signal)
TMVA::PDF*TMVA::MethodBase::fSplBPDFs of MVA distribution (background)
TSpline*TMVA::MethodBase::fSpleffBvsSsplines for signal eff. versus background eff.
TGraph*TMVA::MethodBase::fGraphTrainSgraphs used for splines for training efficiency (signal)
TGraph*TMVA::MethodBase::fGraphTrainBgraphs used for splines for training efficiency (background)
TGraph*TMVA::MethodBase::fGraphTrainEffBvsSgraphs used for splines for training signal eff. versus background eff.
TMVA::PDF*TMVA::MethodBase::fSplTrainSPDFs of training MVA distribution (signal)
TMVA::PDF*TMVA::MethodBase::fSplTrainBPDFs of training MVA distribution (background)
TSpline*TMVA::MethodBase::fSplTrainEffBvsSsplines for training signal eff. versus background eff.
Int_tTMVA::MethodBase::fNbinsnumber of bins in representative histograms
Int_tTMVA::MethodBase::fNbinsHnumber of bins in evaluation histograms
TMVA::MethodBase::ECutOrientationTMVA::MethodBase::fCutOrientation+1 if Sig>Bkg, -1 otherwise
TMVA::TSpline1*TMVA::MethodBase::fSplRefShelper splines for RootFinder (signal)
TMVA::TSpline1*TMVA::MethodBase::fSplRefBhelper splines for RootFinder (background)
TMVA::TSpline1*TMVA::MethodBase::fSplTrainRefShelper splines for RootFinder (signal)
TMVA::TSpline1*TMVA::MethodBase::fSplTrainRefBhelper splines for RootFinder (background)
TMVA::OptionBase*TMVA::MethodBase::fLastDeclaredOptionlast declared option
TListTMVA::MethodBase::fListOfOptionsoption list
TMVA::MsgLoggerTMVA::MethodBase::fLoggermessage logger

Class Description

                                                                      
 ... description of bayesian classifiers ...
_______________________________________________________________________
MethodBayesClassifier( TString jobName, TString methodTitle, DataSet& theData, TString theOption, TDirectory* theTargetDir )
 standard constructor
MethodBayesClassifier( DataSet& theData, TString theWeightFile, TDirectory* theTargetDir )
 constructor from weight file
void InitBayesClassifier( void )
 default initialisation
void DeclareOptions()
 define the options (their key words) that can be set in the option string
void ProcessOptions()
 the option string is decoded, for availabel options see "DeclareOptions"
~MethodBayesClassifier( void )
 destructor
void Train( void )
 some training
void WriteWeightsToStream( ostream & o )
 write the weight from the training to a file (stream)
void ReadWeightsFromStream( istream & istr )
 read back the training results from a file (stream)
Double_t GetMvaValue()
 returns MVA value for given event
const Ranking* CreateRanking()
 ranking of input variables
{ return 0; }

Author: Marcin ....
Last update: root/tmva $Id: MethodBayesClassifier.cxx,v 1.4 2006/11/20 15:35:28 brun Exp $
Copyright (c) 2005-2006: *

ROOT page - Class index - Class Hierarchy - Top of the page
This page has been automatically generated. If you have any comments or suggestions about the page layout send a mail to ROOT support, or contact the developers with any questions or problems regarding ROOT.