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class TMVA::MethodKNN: public TMVA::MethodBase


MethodKNN

Analysis of k-nearest neighbor

Function Members (Methods)

public:

virtual	~MethodKNN()
void	TObject::AbstractMethod(const char* method) const
void	TMVA::Configurable::AddOptionsXMLTo(void* parent) const
void	TMVA::MethodBase::AddOutput(TMVA::Types::ETreeType type, TMVA::Types::EAnalysisType analysisType)
virtual void	AddWeightsXMLTo(void* parent) const
virtual void	TObject::AppendPad(Option_t* option = "")
TDirectory*	TMVA::MethodBase::BaseDir() const
virtual void	TObject::Browse(TBrowser* b)
void	TMVA::Configurable::CheckForUnusedOptions() const
virtual void	TMVA::MethodBase::CheckSetup()
static TClass*	Class()
virtual const char*	TObject::ClassName() const
virtual void	TObject::Clear(Option_t* = "")
virtual TObject*	TObject::Clone(const char* newname = "") const
virtual Int_t	TObject::Compare(const TObject* obj) const
TMVA::Configurable	TMVA::Configurable::Configurable(const TString& theOption = "")
virtual void	TObject::Copy(TObject& object) const
virtual const TMVA::Ranking*	CreateRanking()
TMVA::DataSet*	TMVA::MethodBase::Data() const
TMVA::DataSetInfo&	TMVA::MethodBase::DataInfo() const
virtual void	TObject::Delete(Option_t* option = "")MENU
void	TMVA::MethodBase::DisableWriting(Bool_t setter)
virtual Int_t	TObject::DistancetoPrimitive(Int_t px, Int_t py)
Bool_t	TMVA::MethodBase::DoMulticlass() const
Bool_t	TMVA::MethodBase::DoRegression() const
virtual void	TObject::Draw(Option_t* option = "")
virtual void	TObject::DrawClass() constMENU
virtual TObject*	TObject::DrawClone(Option_t* option = "") constMENU
virtual void	TObject::Dump() constMENU
virtual void	TObject::Error(const char* method, const char* msgfmt) const
virtual void	TObject::Execute(const char* method, const char* params, Int_t* error = 0)
virtual void	TObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0)
virtual void	TObject::ExecuteEvent(Int_t event, Int_t px, Int_t py)
virtual void	TObject::Fatal(const char* method, const char* msgfmt) const
virtual TObject*	TObject::FindObject(const char* name) const
virtual TObject*	TObject::FindObject(const TObject* obj) const
TMVA::Types::EAnalysisType	TMVA::MethodBase::GetAnalysisType() const
const char*	TMVA::Configurable::GetConfigDescription() const
const char*	TMVA::Configurable::GetConfigName() const
virtual Option_t*	TObject::GetDrawOption() const
static Long_t	TObject::GetDtorOnly()
virtual Double_t	TMVA::MethodBase::GetEfficiency(const TString&, TMVA::Types::ETreeType, Double_t& err)
const TMVA::Event*	TMVA::MethodBase::GetEvent() const
const TMVA::Event*	TMVA::MethodBase::GetEvent(const TMVA::Event* ev) const
const TMVA::Event*	TMVA::MethodBase::GetEvent(Long64_t ievt) const
const TMVA::Event*	TMVA::MethodBase::GetEvent(Long64_t ievt, TMVA::Types::ETreeType type) const
const vector<TMVA::Event*>&	TMVA::MethodBase::GetEventCollection(TMVA::Types::ETreeType type)
virtual const char*	TObject::GetIconName() const
const TString&	TMVA::MethodBase::GetInputLabel(Int_t i) const
const TString&	TMVA::MethodBase::GetInputTitle(Int_t i) const
const TString&	TMVA::MethodBase::GetInputVar(Int_t i) const
const TString&	TMVA::MethodBase::GetJobName() const
virtual Double_t	TMVA::MethodBase::GetKSTrainingVsTest(Char_t SorB, TString opt = "X")
virtual Double_t	TMVA::MethodBase::GetMaximumSignificance(Double_t SignalEvents, Double_t BackgroundEvents, Double_t& optimal_significance_value) const
Double_t	TMVA::MethodBase::GetMean(Int_t ivar) const
const TString&	TMVA::MethodBase::GetMethodName() const
TMVA::Types::EMVA	TMVA::MethodBase::GetMethodType() const
TString	TMVA::MethodBase::GetMethodTypeName() const
virtual vector<Float_t>	TMVA::MethodBase::GetMulticlassEfficiency(vector<std::vector<Float_t> >& purity)
virtual vector<Float_t>	TMVA::MethodBase::GetMulticlassTrainingEfficiency(vector<std::vector<Float_t> >& purity)
virtual const vector<Float_t>&	TMVA::MethodBase::GetMulticlassValues()
virtual Double_t	GetMvaValue(Double_t* err = 0, Double_t* errUpper = 0)
virtual const char*	TMVA::MethodBase::GetName() const
UInt_t	TMVA::MethodBase::GetNEvents() const
UInt_t	TMVA::MethodBase::GetNTargets() const
UInt_t	TMVA::MethodBase::GetNvar() const
UInt_t	TMVA::MethodBase::GetNVariables() const
virtual char*	TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_t	TObject::GetObjectStat()
virtual Option_t*	TObject::GetOption() const
const TString&	TMVA::Configurable::GetOptions() const
virtual Double_t	TMVA::MethodBase::GetProba(const TMVA::Event* ev)
virtual Double_t	TMVA::MethodBase::GetProba(Double_t mvaVal, Double_t ap_sig)
const TString	TMVA::MethodBase::GetProbaName() const
virtual Double_t	TMVA::MethodBase::GetRarity(Double_t mvaVal, TMVA::Types::ESBType reftype = Types::kBackground) const
virtual void	TMVA::MethodBase::GetRegressionDeviation(UInt_t tgtNum, TMVA::Types::ETreeType type, Double_t& stddev, Double_t& stddev90Percent) const
virtual const vector<Float_t>&	GetRegressionValues()
Double_t	TMVA::MethodBase::GetRMS(Int_t ivar) const
virtual Double_t	TMVA::MethodBase::GetROCIntegral(TH1D* histS, TH1D* histB) const
virtual Double_t	TMVA::MethodBase::GetROCIntegral(TMVA::PDF* pdfS = 0, TMVA::PDF* pdfB = 0) const
virtual Double_t	TMVA::MethodBase::GetSeparation(TH1, TH1) const
virtual Double_t	TMVA::MethodBase::GetSeparation(TMVA::PDF* pdfS = 0, TMVA::PDF* pdfB = 0) const
Double_t	TMVA::MethodBase::GetSignalReferenceCut() const
Double_t	TMVA::MethodBase::GetSignalReferenceCutOrientation() const
virtual Double_t	TMVA::MethodBase::GetSignificance() const
const TMVA::Event*	TMVA::MethodBase::GetTestingEvent(Long64_t ievt) const
Double_t	TMVA::MethodBase::GetTestTime() const
const TString&	TMVA::MethodBase::GetTestvarName() const
virtual const char*	TObject::GetTitle() const
virtual Double_t	TMVA::MethodBase::GetTrainingEfficiency(const TString&)
const TMVA::Event*	TMVA::MethodBase::GetTrainingEvent(Long64_t ievt) const
UInt_t	TMVA::MethodBase::GetTrainingROOTVersionCode() const
TString	TMVA::MethodBase::GetTrainingROOTVersionString() const
UInt_t	TMVA::MethodBase::GetTrainingTMVAVersionCode() const
TString	TMVA::MethodBase::GetTrainingTMVAVersionString() const
Double_t	TMVA::MethodBase::GetTrainTime() const
TMVA::TransformationHandler&	TMVA::MethodBase::GetTransformationHandler(Bool_t takeReroutedIfAvailable = true)
const TMVA::TransformationHandler&	TMVA::MethodBase::GetTransformationHandler(Bool_t takeReroutedIfAvailable = true) const
virtual UInt_t	TObject::GetUniqueID() const
TString	TMVA::MethodBase::GetWeightFileName() const
Double_t	TMVA::MethodBase::GetXmax(Int_t ivar) const
Double_t	TMVA::MethodBase::GetXmin(Int_t ivar) const
virtual Bool_t	TObject::HandleTimer(TTimer* timer)
virtual Bool_t	HasAnalysisType(TMVA::Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
virtual ULong_t	TObject::Hash() const
Bool_t	TMVA::MethodBase::HasMVAPdfs() const
virtual void	TObject::Info(const char* method, const char* msgfmt) const
virtual Bool_t	TObject::InheritsFrom(const char* classname) const
virtual Bool_t	TObject::InheritsFrom(const TClass* cl) const
virtual void	TObject::Inspect() constMENU
void	TObject::InvertBit(UInt_t f)
virtual TClass*	IsA() const
virtual Bool_t	TObject::IsEqual(const TObject* obj) const
virtual Bool_t	TObject::IsFolder() const
Bool_t	TObject::IsOnHeap() const
virtual Bool_t	TMVA::MethodBase::IsSignalLike()
virtual Bool_t	TMVA::MethodBase::IsSignalLike(Double_t mvaVal)
virtual Bool_t	TObject::IsSortable() const
Bool_t	TObject::IsZombie() const
virtual void	TObject::ls(Option_t* option = "") const
virtual void	TMVA::MethodBase::MakeClass(const TString& classFileName = TString("")) const
void	TObject::MayNotUse(const char* method) const
TDirectory*	TMVA::MethodBase::MethodBaseDir() const
TMVA::MethodKNN	MethodKNN(TMVA::DataSetInfo& theData, const TString& theWeightFile, TDirectory* theTargetDir = NULL)
TMVA::MethodKNN	MethodKNN(const TString& jobName, const TString& methodTitle, TMVA::DataSetInfo& theData, const TString& theOption = "KNN", TDirectory* theTargetDir = NULL)
virtual Bool_t	TObject::Notify()
void	TObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
static void	TObject::operator delete(void* ptr)
static void	TObject::operator delete(void* ptr, void* vp)
static void	TObject::operator delete[](void* ptr)
static void	TObject::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 map<TString,Double_t>	TMVA::MethodBase::OptimizeTuningParameters(TString fomType = "ROCIntegral", TString fitType = "FitGA")
virtual void	TObject::Paint(Option_t* option = "")
virtual void	TMVA::Configurable::ParseOptions()
virtual void	TObject::Pop()
virtual void	TObject::Print(Option_t* option = "") const
virtual void	TMVA::MethodBase::PrintHelpMessage() const
void	TMVA::Configurable::PrintOptions() const
void	TMVA::MethodBase::ProcessSetup()
virtual Int_t	TObject::Read(const char* name)
void	TMVA::Configurable::ReadOptionsFromStream(istream& istr)
void	TMVA::Configurable::ReadOptionsFromXML(void* node)
void	TMVA::MethodBase::ReadStateFromFile()
void	TMVA::MethodBase::ReadStateFromStream(istream& tf)
void	TMVA::MethodBase::ReadStateFromStream(TFile& rf)
void	TMVA::MethodBase::ReadStateFromXMLString(const char* xmlstr)
virtual void	ReadWeightsFromStream(istream& istr)
virtual void	ReadWeightsFromStream(TFile& rf)
virtual void	ReadWeightsFromXML(void* wghtnode)
virtual void	TObject::RecursiveRemove(TObject* obj)
void	TMVA::MethodBase::RerouteTransformationHandler(TMVA::TransformationHandler* fTargetTransformation)
virtual void	TMVA::MethodBase::Reset()
void	TObject::ResetBit(UInt_t f)
virtual void	TObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual void	TObject::SavePrimitive(ostream& out, Option_t* option = "")
virtual void	TMVA::MethodBase::SetAnalysisType(TMVA::Types::EAnalysisType type)
void	TMVA::MethodBase::SetBaseDir(TDirectory* methodDir)
void	TObject::SetBit(UInt_t f)
void	TObject::SetBit(UInt_t f, Bool_t set)
void	TMVA::Configurable::SetConfigDescription(const char* d)
void	TMVA::Configurable::SetConfigName(const char* n)
virtual void	TObject::SetDrawOption(Option_t* option = "")MENU
static void	TObject::SetDtorOnly(void* obj)
void	TMVA::MethodBase::SetMethodBaseDir(TDirectory* methodDir)
void	TMVA::MethodBase::SetMethodDir(TDirectory* methodDir)
void	TMVA::Configurable::SetMsgType(TMVA::EMsgType t)
static void	TObject::SetObjectStat(Bool_t stat)
void	TMVA::Configurable::SetOptions(const TString& s)
void	TMVA::MethodBase::SetSignalReferenceCut(Double_t cut)
void	TMVA::MethodBase::SetSignalReferenceCutOrientation(Double_t cutOrientation)
void	TMVA::MethodBase::SetTestTime(Double_t testTime)
void	TMVA::MethodBase::SetTestvarName(const TString& v = "")
void	TMVA::MethodBase::SetTrainTime(Double_t trainTime)
virtual void	TMVA::MethodBase::SetTuneParameters(map<TString,Double_t> tuneParameters)
virtual void	TObject::SetUniqueID(UInt_t uid)
void	TMVA::MethodBase::SetupMethod()
virtual void	ShowMembers(TMemberInspector&)
virtual void	Streamer(TBuffer&)
void	StreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)
virtual void	TObject::SysError(const char* method, const char* msgfmt) const
Bool_t	TObject::TestBit(UInt_t f) const
Int_t	TObject::TestBits(UInt_t f) const
virtual void	TMVA::MethodBase::TestClassification()
virtual void	TMVA::MethodBase::TestMulticlass()
virtual void	TMVA::MethodBase::TestRegression(Double_t& bias, Double_t& biasT, Double_t& dev, Double_t& devT, Double_t& rms, Double_t& rmsT, Double_t& mInf, Double_t& mInfT, Double_t& corr, TMVA::Types::ETreeType type)
virtual void	Train()
void	TMVA::MethodBase::TrainMethod()
virtual void	TObject::UseCurrentStyle()
virtual void	TObject::Warning(const char* method, const char* msgfmt) const
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0)
virtual Int_t	TObject::Write(const char* name = 0, Int_t option = 0, Int_t bufsize = 0) const
virtual void	TMVA::MethodBase::WriteEvaluationHistosToFile(TMVA::Types::ETreeType treetype)
virtual void	TMVA::MethodBase::WriteMonitoringHistosToFile() const
void	TMVA::Configurable::WriteOptionsToStream(ostream& o, const TString& prefix) const
void	TMVA::MethodBase::WriteStateToFile() const
void	WriteWeightsToStream(TFile& rf) const

protected:

virtual void	TObject::DoError(int level, const char* location, const char* fmt, va_list va) const
void	TMVA::Configurable::EnableLooseOptions(Bool_t b = kTRUE)
virtual void	GetHelpMessage() const
const TString&	TMVA::MethodBase::GetInternalVarName(Int_t ivar) const
const TString&	TMVA::MethodBase::GetOriginalVarName(Int_t ivar) const
const TString&	TMVA::Configurable::GetReferenceFile() const
static TMVA::MethodBase*	TMVA::MethodBase::GetThisBase()
const TString&	TMVA::MethodBase::GetWeightFileDir() const
Bool_t	TMVA::MethodBase::HasTrainingTree() const
Bool_t	TMVA::MethodBase::Help() const
Bool_t	TMVA::MethodBase::IgnoreEventsWithNegWeightsInTraining() const
Bool_t	TMVA::MethodBase::IsConstructedFromWeightFile() const
Bool_t	TMVA::MethodBase::IsNormalised() const
TMVA::MsgLogger&	TMVA::Configurable::Log() const
Bool_t	TMVA::Configurable::LooseOptionCheckingEnabled() const
virtual void	MakeClassSpecific(ostream&, const TString&) const
virtual void	TMVA::MethodBase::MakeClassSpecificHeader(ostream&, const TString& = "") const
void	TObject::MakeZombie()
void	TMVA::MethodBase::NoErrorCalc(Double_t const err, Double_t const errUpper)
void	TMVA::Configurable::ResetSetFlag()
void	TMVA::MethodBase::SetNormalised(Bool_t norm)
void	TMVA::MethodBase::SetWeightFileDir(TString fileDir)
void	TMVA::MethodBase::SetWeightFileName(TString)
void	TMVA::MethodBase::Statistics(TMVA::Types::ETreeType treeType, const TString& theVarName, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&)
Bool_t	TMVA::MethodBase::TxtWeightsOnly() const
Bool_t	TMVA::MethodBase::Verbose() const
void	TMVA::Configurable::WriteOptionsReferenceToFile()

private:

virtual void	DeclareCompatibilityOptions()
virtual void	DeclareOptions()
Double_t	GausKernel(const TMVA::kNN::Event& event_knn, const TMVA::kNN::Event& event, const vector<Double_t>& svec) const
Double_t	getKernelRadius(const list<pair<const TMVA::kNN::Node<TMVA::kNN::Event>,float>,allocator<pair<const TMVA::kNN::Node<TMVA::kNN::Event>,float> > >& rlist) const
double	getLDAValue(const list<pair<const TMVA::kNN::Node<TMVA::kNN::Event>,float>,allocator<pair<const TMVA::kNN::Node<TMVA::kNN::Event>,float> > >& rlist, const TMVA::kNN::Event& event_knn)
const vector<Double_t>	getRMS(const list<pair<const TMVA::kNN::Node<TMVA::kNN::Event>,float>,allocator<pair<const TMVA::kNN::Node<TMVA::kNN::Event>,float> > >& rlist, const TMVA::kNN::Event& event_knn) const
virtual void	Init()
void	MakeKNN()
Double_t	PolnKernel(Double_t value) const
virtual void	ProcessOptions()

Data Members

public:

enum TMVA::MethodBase::EWeightFileType {	kROOT
	kTEXT
};
enum TObject::EStatusBits {	kCanDelete
	kMustCleanup
	kObjInCanvas
	kIsReferenced
	kHasUUID
	kCannotPick
	kNoContextMenu
	kInvalidObject
};
enum TObject::[unnamed] {	kIsOnHeap
	kNotDeleted
	kZombie
	kBitMask
	kSingleKey
	kOverwrite
	kWriteDelete
};

public:

Bool_t	TMVA::MethodBase::fSetupCompleted	is method setup
const TMVA::Event*	TMVA::MethodBase::fTmpEvent	! temporary event when testing on a different DataSet than the own one

protected:

TMVA::Types::EAnalysisType	TMVA::MethodBase::fAnalysisType	method-mode : true --> regression, false --> classification
UInt_t	TMVA::MethodBase::fBackgroundClass	index of the Background-class
vector<TString>*	TMVA::MethodBase::fInputVars	vector of input variables used in MVA
vector<Float_t>*	TMVA::MethodBase::fMulticlassReturnVal	holds the return-values for the multiclass classification
Int_t	TMVA::MethodBase::fNbins	number of bins in input variable histograms
Int_t	TMVA::MethodBase::fNbinsH	number of bins in evaluation histograms
Int_t	TMVA::MethodBase::fNbinsMVAoutput	number of bins in MVA output histograms
TMVA::Ranking*	TMVA::MethodBase::fRanking	pointer to ranking object (created by derived classifiers)
vector<Float_t>*	TMVA::MethodBase::fRegressionReturnVal	holds the return-values for the regression
UInt_t	TMVA::MethodBase::fSignalClass	index of the Signal-class

private:

Int_t	fBalanceDepth	number of binary tree levels used for balancing tree
vector<TMVA::kNN::Event,allocator<TMVA::kNN::Event> >	fEvent	! (untouched) events used for learning
TString	fKernel	="Gaus","Poln" - kernel type for smoothing
TMVA::LDA	fLDA	! Experimental feature for local knn analysis
TMVA::kNN::ModulekNN*	fModule	! module where all work is done
Float_t	fScaleFrac	fraction of events used to compute variable width
Float_t	fSigmaFact	scale factor for Gaussian sigma in Gaus. kernel
Double_t	fSumOfWeightsB	sum-of-weights for background training events
Double_t	fSumOfWeightsS	sum-of-weights for signal training events
Int_t	fTreeOptDepth	number of binary tree levels used for optimization
Bool_t	fTrim	set equal number of signal and background events
Bool_t	fUseKernel	use polynomial kernel weight function
Bool_t	fUseLDA	use local linear discriminat analysis to compute MVA
Bool_t	fUseWeight	use weights to count kNN
Int_t	fnkNN	number of k-nearest neighbors

Class Charts

Inheritance Inherited Members Includes Libraries

Function documentation

MethodKNN(const TString& jobName, const TString& methodTitle, TMVA::DataSetInfo& theData, const TString& theOption = "KNN", TDirectory* theTargetDir = NULL)

 standard constructor

MethodKNN(TMVA::DataSetInfo& theData, const TString& theWeightFile, TDirectory* theTargetDir = NULL)

 constructor from weight file

~MethodKNN()

 destructor

void DeclareOptions()

 MethodKNN options

void DeclareCompatibilityOptions()

 options that are used ONLY for the READER to ensure backward compatibility

void ProcessOptions()

 process the options specified by the user

Bool_t HasAnalysisType(TMVA::Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)

 FDA can handle classification with 2 classes and regression with one regression-target

void Init()

 Initialization

void MakeKNN()

 create kNN

void Train()

 kNN training

Double_t GetMvaValue(Double_t* err = 0, Double_t* errUpper = 0)

 Compute classifier response

const std::vector< Float_t >& GetRegressionValues()

 Return vector of averages for target values of k-nearest neighbors.
 Use own copy of the regression vector, I do not like using a pointer to vector.

const TMVA::Ranking* CreateRanking()

 no ranking available

void AddWeightsXMLTo(void* parent) const

 write weights to XML

void ReadWeightsFromXML(void* wghtnode)

void ReadWeightsFromStream(istream& istr)

 read the weights

void WriteWeightsToStream(TFile& rf) const

 save weights to ROOT file

void ReadWeightsFromStream(TFile& rf)

 read weights from ROOT file

void MakeClassSpecific(ostream& , const TString& ) const

 write specific classifier response

void GetHelpMessage() const

 get help message text

 typical length of text line:
         "|--------------------------------------------------------------|"

Double_t PolnKernel(Double_t value) const

 polynomial kernel

Double_t GausKernel(const TMVA::kNN::Event& event_knn, const TMVA::kNN::Event& event, const vector<Double_t>& svec) const

 Gaussian kernel

Double_t getKernelRadius(const list<pair<const TMVA::kNN::Node<TMVA::kNN::Event>*,float>,allocator<pair<const TMVA::kNN::Node<TMVA::kNN::Event>*,float> > >& rlist) const

 Get polynomial kernel radius

const std::vector<Double_t> getRMS(const list<pair<const TMVA::kNN::Node<TMVA::kNN::Event>*,float>,allocator<pair<const TMVA::kNN::Node<TMVA::kNN::Event>*,float> > >& rlist, const TMVA::kNN::Event& event_knn) const

 Get polynomial kernel radius

Double_t getLDAValue(const list<pair<const TMVA::kNN::Node<TMVA::kNN::Event>*,float>,allocator<pair<const TMVA::kNN::Node<TMVA::kNN::Event>*,float> > >& rlist, const TMVA::kNN::Event& event_knn)