A++ » TMVA » TMVA::MethodANNBase

class TMVA::MethodANNBase: public TMVA::MethodBase


MethodANNBase

Base class for all TMVA methods using artificial neural networks

Function Members (Methods)

 
    This is an abstract class, constructors will not be documented.
    Look at the header to check for available constructors.
public:
virtual~MethodANNBase()
voidTObject::AbstractMethod(const char* method) const
voidTMVA::Configurable::AddOptionsXMLTo(void* parent) const
voidTMVA::MethodBase::AddOutput(TMVA::Types::ETreeType type, TMVA::Types::EAnalysisType analysisType)
virtual voidAddWeightsXMLTo(void* parent) const
virtual voidTObject::AppendPad(Option_t* option = "")
TDirectory*TMVA::MethodBase::BaseDir() const
virtual voidTObject::Browse(TBrowser* b)
voidTMVA::Configurable::CheckForUnusedOptions() const
virtual voidTMVA::MethodBase::CheckSetup()
static TClass*Class()
virtual const char*TObject::ClassName() const
virtual voidTNamed::Clear(Option_t* option = "")
virtual TObject*TNamed::Clone(const char* newname = "") const
virtual Int_tTNamed::Compare(const TObject* obj) const
TMVA::ConfigurableTMVA::Configurable::Configurable(const TString& theOption = "")
TMVA::ConfigurableTMVA::Configurable::Configurable(const TMVA::Configurable&)
virtual voidTNamed::Copy(TObject& named) const
virtual const TMVA::Ranking*CreateRanking()
TMVA::DataSet*TMVA::MethodBase::Data() const
TMVA::DataSetInfo&TMVA::MethodBase::DataInfo() const
Bool_tDebug() const
virtual voidTMVA::MethodBase::DeclareCompatibilityOptions()
virtual voidDeclareOptions()
virtual voidTObject::Delete(Option_t* option = "")MENU
voidTMVA::MethodBase::DisableWriting(Bool_t setter)
virtual Int_tTObject::DistancetoPrimitive(Int_t px, Int_t py)
Bool_tTMVA::MethodBase::DoMulticlass() const
Bool_tTMVA::MethodBase::DoRegression() const
virtual voidTObject::Draw(Option_t* option = "")
virtual voidTObject::DrawClass() constMENU
virtual TObject*TObject::DrawClone(Option_t* option = "") constMENU
virtual voidTObject::Dump() constMENU
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)
voidTMVA::MethodBase::ExitFromTraining()
virtual voidTObject::Fatal(const char* method, const char* msgfmt) const
virtual voidTNamed::FillBuffer(char*& buffer)
virtual TObject*TObject::FindObject(const char* name) const
virtual TObject*TObject::FindObject(const TObject* obj) const
TMVA::Types::EAnalysisTypeTMVA::MethodBase::GetAnalysisType() const
const char*TMVA::Configurable::GetConfigDescription() const
const char*TMVA::Configurable::GetConfigName() const
UInt_tTMVA::MethodBase::GetCurrentIter()
virtual Option_t*TObject::GetDrawOption() const
static Long_tTObject::GetDtorOnly()
virtual Double_tTMVA::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)
TFile*TMVA::MethodBase::GetFile() const
virtual const char*TObject::GetIconName() const
const TString&TMVA::MethodBase::GetInputLabel(Int_t i) const
const char*TMVA::MethodBase::GetInputTitle(Int_t i) const
const TString&TMVA::MethodBase::GetInputVar(Int_t i) const
TMultiGraph*TMVA::MethodBase::GetInteractiveTrainingError()
const TString&TMVA::MethodBase::GetJobName() const
virtual Double_tTMVA::MethodBase::GetKSTrainingVsTest(Char_t SorB, TString opt = "X")
virtual Double_tTMVA::MethodBase::GetMaximumSignificance(Double_t SignalEvents, Double_t BackgroundEvents, Double_t& optimal_significance_value) const
UInt_tTMVA::MethodBase::GetMaxIter()
Double_tTMVA::MethodBase::GetMean(Int_t ivar) const
const TString&TMVA::MethodBase::GetMethodName() const
TMVA::Types::EMVATMVA::MethodBase::GetMethodType() const
TStringTMVA::MethodBase::GetMethodTypeName() const
virtual vector<Float_t>TMVA::MethodBase::GetMulticlassEfficiency(vector<vector<Float_t> >& purity)
virtual vector<Float_t>TMVA::MethodBase::GetMulticlassTrainingEfficiency(vector<vector<Float_t> >& purity)
virtual const vector<Float_t>&GetMulticlassValues()
virtual Double_tGetMvaValue(Double_t* err = 0, Double_t* errUpper = 0)
virtual const char*TMVA::MethodBase::GetName() const
UInt_tTMVA::MethodBase::GetNEvents() const
UInt_tTMVA::MethodBase::GetNTargets() const
UInt_tTMVA::MethodBase::GetNvar() const
UInt_tTMVA::MethodBase::GetNVariables() const
virtual char*TObject::GetObjectInfo(Int_t px, Int_t py) const
static Bool_tTObject::GetObjectStat()
virtual Option_t*TObject::GetOption() const
const TString&TMVA::Configurable::GetOptions() const
virtual Double_tTMVA::MethodBase::GetProba(const TMVA::Event* ev)
virtual Double_tTMVA::MethodBase::GetProba(Double_t mvaVal, Double_t ap_sig)
const TStringTMVA::MethodBase::GetProbaName() const
virtual Double_tTMVA::MethodBase::GetRarity(Double_t mvaVal, TMVA::Types::ESBType reftype = Types::kBackground) const
virtual voidTMVA::MethodBase::GetRegressionDeviation(UInt_t tgtNum, TMVA::Types::ETreeType type, Double_t& stddev, Double_t& stddev90Percent) const
virtual const vector<Float_t>&GetRegressionValues()
Double_tTMVA::MethodBase::GetRMS(Int_t ivar) const
virtual Double_tTMVA::MethodBase::GetROCIntegral(TH1D* histS, TH1D* histB) const
virtual Double_tTMVA::MethodBase::GetROCIntegral(TMVA::PDF* pdfS = 0, TMVA::PDF* pdfB = 0) const
virtual Double_tTMVA::MethodBase::GetSeparation(TH1*, TH1*) const
virtual Double_tTMVA::MethodBase::GetSeparation(TMVA::PDF* pdfS = 0, TMVA::PDF* pdfB = 0) const
Double_tTMVA::MethodBase::GetSignalReferenceCut() const
Double_tTMVA::MethodBase::GetSignalReferenceCutOrientation() const
virtual Double_tTMVA::MethodBase::GetSignificance() const
const TMVA::Event*TMVA::MethodBase::GetTestingEvent(Long64_t ievt) const
Double_tTMVA::MethodBase::GetTestTime() const
const TString&TMVA::MethodBase::GetTestvarName() const
virtual const char*TNamed::GetTitle() const
virtual Double_tTMVA::MethodBase::GetTrainingEfficiency(const TString&)
const TMVA::Event*TMVA::MethodBase::GetTrainingEvent(Long64_t ievt) const
UInt_tTMVA::MethodBase::GetTrainingROOTVersionCode() const
TStringTMVA::MethodBase::GetTrainingROOTVersionString() const
UInt_tTMVA::MethodBase::GetTrainingTMVAVersionCode() const
TStringTMVA::MethodBase::GetTrainingTMVAVersionString() const
Double_tTMVA::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_tTObject::GetUniqueID() const
TStringTMVA::MethodBase::GetWeightFileName() const
Double_tTMVA::MethodBase::GetXmax(Int_t ivar) const
Double_tTMVA::MethodBase::GetXmin(Int_t ivar) const
virtual Bool_tTObject::HandleTimer(TTimer* timer)
virtual Bool_tTMVA::IMethod::HasAnalysisType(TMVA::Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
virtual ULong_tTNamed::Hash() const
Bool_tTMVA::MethodBase::HasMVAPdfs() const
TMVA::IMethodTMVA::IMethod::IMethod()
TMVA::IMethodTMVA::IMethod::IMethod(const TMVA::IMethod&)
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
virtual voidTMVA::MethodBase::Init()
voidInitANNBase()
voidTMVA::MethodBase::InitIPythonInteractive()
virtual voidTObject::Inspect() constMENU
voidTObject::InvertBit(UInt_t f)
virtual TClass*IsA() const
virtual Bool_tTObject::IsEqual(const TObject* obj) const
virtual Bool_tTObject::IsFolder() const
Bool_tTMVA::MethodBase::IsModelPersistence()
Bool_tTObject::IsOnHeap() const
virtual Bool_tTMVA::MethodBase::IsSignalLike()
virtual Bool_tTMVA::MethodBase::IsSignalLike(Double_t mvaVal)
Bool_tTMVA::MethodBase::IsSilentFile()
virtual Bool_tTNamed::IsSortable() const
Bool_tTObject::IsZombie() const
TMVA::MsgLogger&TMVA::Configurable::Log() const
virtual voidTNamed::ls(Option_t* option = "") const
virtual voidTMVA::MethodBase::MakeClass(const TString& classFileName = TString("")) const
voidTObject::MayNotUse(const char* method) const
TMVA::MethodANNBaseMethodANNBase(const TMVA::MethodANNBase&)
TMVA::MethodANNBaseMethodANNBase(TMVA::Types::EMVA methodType, TMVA::DataSetInfo& theData, const TString& theWeightFile)
TMVA::MethodANNBaseMethodANNBase(const TString& jobName, TMVA::Types::EMVA methodType, const TString& methodTitle, TMVA::DataSetInfo& theData, const TString& theOption)
TMVA::MethodBaseTMVA::MethodBase::MethodBase(const TMVA::MethodBase&)
TMVA::MethodBaseTMVA::MethodBase::MethodBase(TMVA::Types::EMVA methodType, TMVA::DataSetInfo& dsi, const TString& weightFile)
TMVA::MethodBaseTMVA::MethodBase::MethodBase(const TString& jobName, TMVA::Types::EMVA methodType, const TString& methodTitle, TMVA::DataSetInfo& dsi, const TString& theOption = "")
TDirectory*TMVA::MethodBase::MethodBaseDir() const
virtual Bool_tTObject::Notify()
voidTObject::Obsolete(const char* method, const char* asOfVers, const char* removedFromVers) const
voidTObject::operator delete(void* ptr)
voidTObject::operator delete(void* ptr, void* vp)
voidTObject::operator delete[](void* ptr)
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::MethodANNBase&operator=(const TMVA::MethodANNBase&)
virtual map<TString,Double_t>TMVA::MethodBase::OptimizeTuningParameters(TString fomType = "ROCIntegral", TString fitType = "FitGA")
virtual voidTObject::Paint(Option_t* option = "")
virtual voidTMVA::Configurable::ParseOptions()
virtual voidTObject::Pop()
virtual voidTNamed::Print(Option_t* option = "") const
virtual voidTMVA::MethodBase::PrintHelpMessage() const
virtual voidPrintNetwork() const
voidTMVA::Configurable::PrintOptions() const
virtual voidProcessOptions()
voidTMVA::MethodBase::ProcessSetup()
virtual Int_tTObject::Read(const char* name)
voidTMVA::Configurable::ReadOptionsFromStream(istream& istr)
voidTMVA::Configurable::ReadOptionsFromXML(void* node)
voidTMVA::MethodBase::ReadStateFromFile()
voidTMVA::MethodBase::ReadStateFromStream(istream& tf)
voidTMVA::MethodBase::ReadStateFromStream(TFile& rf)
voidTMVA::MethodBase::ReadStateFromXMLString(const char* xmlstr)
virtual voidReadWeightsFromStream(istream& istr)
virtual voidReadWeightsFromXML(void* wghtnode)
virtual voidTObject::RecursiveRemove(TObject* obj)
voidTMVA::MethodBase::RerouteTransformationHandler(TMVA::TransformationHandler* fTargetTransformation)
virtual voidTMVA::MethodBase::Reset()
voidTObject::ResetBit(UInt_t f)
virtual voidTObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU
virtual voidTObject::SavePrimitive(ostream& out, Option_t* option = "")
voidSetActivation(TMVA::TActivation* activation)
virtual voidTMVA::MethodBase::SetAnalysisType(TMVA::Types::EAnalysisType type)
voidTMVA::MethodBase::SetBaseDir(TDirectory* methodDir)
voidTObject::SetBit(UInt_t f)
voidTObject::SetBit(UInt_t f, Bool_t set)
voidTMVA::Configurable::SetConfigDescription(const char* d)
voidTMVA::Configurable::SetConfigName(const char* n)
virtual voidTObject::SetDrawOption(Option_t* option = "")MENU
static voidTObject::SetDtorOnly(void* obj)
voidTMVA::MethodBase::SetFile(TFile* file)
voidTMVA::MethodBase::SetMethodBaseDir(TDirectory* methodDir)
voidTMVA::MethodBase::SetMethodDir(TDirectory* methodDir)
voidTMVA::MethodBase::SetModelPersistence(Bool_t status)
voidTMVA::Configurable::SetMsgType(TMVA::EMsgType t)
virtual voidTNamed::SetName(const char* name)MENU
virtual voidTNamed::SetNameTitle(const char* name, const char* title)
voidSetNeuronInputCalculator(TMVA::TNeuronInput* inputCalculator)
static voidTObject::SetObjectStat(Bool_t stat)
voidTMVA::Configurable::SetOptions(const TString& s)
voidTMVA::MethodBase::SetSignalReferenceCut(Double_t cut)
voidTMVA::MethodBase::SetSignalReferenceCutOrientation(Double_t cutOrientation)
voidTMVA::MethodBase::SetSilentFile(Bool_t status)
voidTMVA::MethodBase::SetTestTime(Double_t testTime)
voidTMVA::MethodBase::SetTestvarName(const TString& v = "")
virtual voidTNamed::SetTitle(const char* title = "")MENU
voidTMVA::MethodBase::SetTrainTime(Double_t trainTime)
virtual voidTMVA::MethodBase::SetTuneParameters(map<TString,Double_t> tuneParameters)
virtual voidTObject::SetUniqueID(UInt_t uid)
voidTMVA::MethodBase::SetupMethod()
virtual voidShowMembers(TMemberInspector& insp) const
virtual Int_tTNamed::Sizeof() const
virtual voidStreamer(TBuffer&)
voidStreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)
virtual voidTObject::SysError(const char* method, const char* msgfmt) const
Bool_tTObject::TestBit(UInt_t f) const
Int_tTObject::TestBits(UInt_t f) const
virtual voidTMVA::MethodBase::TestClassification()
virtual voidTMVA::MethodBase::TestMulticlass()
virtual voidTMVA::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 voidTrain()
boolTMVA::MethodBase::TrainingEnded()
voidTMVA::MethodBase::TrainMethod()
virtual voidTObject::UseCurrentStyle()
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(TMVA::Types::ETreeType treetype)
virtual voidWriteMonitoringHistosToFile() const
voidTMVA::Configurable::WriteOptionsToStream(ostream& o, const TString& prefix) const
voidTMVA::MethodBase::WriteStateToFile() const
protected:
virtual voidBuildNetwork(vector<Int_t>* layout, vector<Double_t>* weights = __null, Bool_t fromFile = kFALSE)
voidCreateWeightMonitoringHists(const TString& bulkname, vector<TH1*>* hv = 0) const
virtual voidTObject::DoError(int level, const char* location, const char* fmt, va_list va) const
voidTMVA::Configurable::EnableLooseOptions(Bool_t b = kTRUE)
voidForceNetworkCalculations()
voidForceNetworkInputs(const TMVA::Event* ev, Int_t ignoreIndex = -1)
virtual voidTMVA::IMethod::GetHelpMessage() const
TMVA::TNeuron*GetInputNeuron(Int_t index)
const TString&TMVA::MethodBase::GetInternalVarName(Int_t ivar) const
virtual vector<Double_t>TMVA::MethodBase::GetMvaValues(Long64_t firstEvt = 0, Long64_t lastEvt = -1, Bool_t logProgress = false)
Double_tGetNetworkOutput()
const TString&TMVA::MethodBase::GetOriginalVarName(Int_t ivar) const
TMVA::TNeuron*GetOutputNeuron(Int_t index = 0)
const TString&TMVA::Configurable::GetReferenceFile() const
const TString&TMVA::MethodBase::GetWeightFileDir() const
Bool_tTMVA::MethodBase::HasTrainingTree() const
Bool_tTMVA::MethodBase::Help() const
Bool_tTMVA::MethodBase::IgnoreEventsWithNegWeightsInTraining() const
Bool_tTMVA::MethodBase::IsConstructedFromWeightFile() const
Bool_tTMVA::MethodBase::IsNormalised() const
Bool_tTMVA::Configurable::LooseOptionCheckingEnabled() const
virtual voidMakeClassSpecific(ostream&, const TString&) const
virtual voidTMVA::MethodBase::MakeClassSpecificHeader(ostream&, const TString& = "") const
voidTObject::MakeZombie()
voidTMVA::MethodBase::NoErrorCalc(Double_t*const err, Double_t*const errUpper)
Int_tNumCycles()
vector<Int_t>*ParseLayoutString(TString layerSpec)
voidPrintMessage(TString message, Bool_t force = kFALSE) const
voidTMVA::Configurable::ResetSetFlag()
voidTMVA::MethodBase::SetNormalised(Bool_t norm)
voidTMVA::MethodBase::SetWeightFileDir(TString fileDir)
voidTMVA::MethodBase::SetWeightFileName(TString)
voidTMVA::MethodBase::Statistics(TMVA::Types::ETreeType treeType, const TString& theVarName, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&, Double_t&)
Bool_tTMVA::MethodBase::TxtWeightsOnly() const
Bool_tTMVA::MethodBase::Verbose() const
voidWaitForKeyboard()
voidTMVA::Configurable::WriteOptionsReferenceToFile()
private:
voidAddPreLinks(TMVA::TNeuron* neuron, TObjArray* prevLayer)
voidBuildLayer(Int_t numNeurons, TObjArray* curLayer, TObjArray* prevLayer, Int_t layerIndex, Int_t numLayers, Bool_t from_file = false)
voidBuildLayers(vector<Int_t>* layout, Bool_t from_file = false)
voidDeleteNetwork()
voidDeleteNetworkLayer(TObjArray*& layer)
voidForceWeights(vector<Double_t>* weights)
voidInitWeights()
voidPrintLayer(TObjArray* layer) const
voidPrintNeuron(TMVA::TNeuron* neuron) const

Data Members

public:
TObjArray*fNetworkTObjArray of TObjArrays representing network
Bool_tTMVA::MethodBase::fSetupCompletedis method setup
const TMVA::Event*TMVA::MethodBase::fTmpEvent! temporary event when testing on a different DataSet than the own one
static TObject::(anonymous)TObject::kBitMask
static TMVA::MethodANNBase::EEstimatorkCE
static TObject::EStatusBitsTObject::kCanDelete
static TObject::EStatusBitsTObject::kCannotPick
static TObject::EStatusBitsTObject::kHasUUID
static TObject::EStatusBitsTObject::kInvalidObject
static TObject::(anonymous)TObject::kIsOnHeap
static TObject::EStatusBitsTObject::kIsReferenced
static TMVA::MethodANNBase::EEstimatorkMSE
static TObject::EStatusBitsTObject::kMustCleanup
static TObject::EStatusBitsTObject::kNoContextMenu
static TObject::(anonymous)TObject::kNotDeleted
static TObject::EStatusBitsTObject::kObjInCanvas
static TObject::(anonymous)TObject::kOverwrite
static TMVA::MethodBase::EWeightFileTypeTMVA::MethodBase::kROOT
static TObject::(anonymous)TObject::kSingleKey
static TMVA::MethodBase::EWeightFileTypeTMVA::MethodBase::kTEXT
static TObject::(anonymous)TObject::kWriteDelete
static TObject::(anonymous)TObject::kZombie
protected:
TMVA::TActivation*fActivationactivation function to be used for hidden layers
TMVA::Types::EAnalysisTypeTMVA::MethodBase::fAnalysisTypemethod-mode : true --> regression, false --> classification
UInt_tTMVA::MethodBase::fBackgroundClassindex of the Background-class
vector<TH1*>fEpochMonHistBepoch monitoring hitograms for background
vector<TH1*>fEpochMonHistSepoch monitoring hitograms for signal
vector<TH1*>fEpochMonHistWepoch monitoring hitograms for weights
TMVA::MethodANNBase::EEstimatorfEstimator
TH1F*fEstimatorHistTestmonitors convergence of independent test sample
TH1F*fEstimatorHistTrainmonitors convergence of training sample
TStringfEstimatorS
boolTMVA::MethodBase::fExitFromTraining
UInt_tTMVA::MethodBase::fIPyCurrentIter
UInt_tTMVA::MethodBase::fIPyMaxIter
TMVA::TActivation*fIdentityactivation for input and output layers
TMVA::TNeuronInput*fInputCalculatorinput calculator for all neurons
vector<TString>*TMVA::MethodBase::fInputVarsvector of input variables used in MVA
TMVA::IPythonInteractive*TMVA::MethodBase::fInteractive
TMatrixDfInvHessianzjh
TMVA::MsgLogger*TMVA::Configurable::fLogger! message logger
vector<Float_t>*TMVA::MethodBase::fMulticlassReturnValholds the return-values for the multiclass classification
TStringTNamed::fNameobject identifier
Int_tTMVA::MethodBase::fNbinsnumber of bins in input variable histograms
Int_tTMVA::MethodBase::fNbinsHnumber of bins in evaluation histograms
Int_tTMVA::MethodBase::fNbinsMVAoutputnumber of bins in MVA output histograms
Int_tfNcyclesnumber of epochs to train
TStringfNeuronInputTypename of neuron input calculator class
TStringfNeuronTypename of neuron activation function class
TMVA::TActivation*fOutputactivation function to be used for output layers, depending on estimator
Int_tfRandomSeedrandom seed for initial synapse weights
TMVA::Ranking*TMVA::MethodBase::fRankingpointer to ranking object (created by derived classifiers)
vector<Float_t>*TMVA::MethodBase::fRegressionReturnValholds the return-values for the regression
vector<Int_t>fRegulatorIdxindex to different priors from every synapses
vector<Double_t>fRegulatorsthe priors as regulator
TMVA::Results*TMVA::MethodBase::fResults
UInt_tTMVA::MethodBase::fSignalClassindex of the Signal-class
TObjArray*fSynapsesarray of pointers to synapses, no structural data
TStringTNamed::fTitleobject title
boolfUseRegulatorzjh
TRandom3*frgenrandom number generator for various uses
private:
TObjArray*fInputLayercache this for fast access
TStringfLayerSpeclayout specification option
vector<TMVA::TNeuron*>fOutputNeuronscache this for fast access
static const Bool_tfgDEBUGdebug flag

Class Charts

Inheritance Chart:
TMVA::IMethod
TObject
←
TNamed
←
TMVA::Configurable
←
TMVA::MethodBase
←
TMVA::MethodANNBase
←
TMVA::MethodMLP

Function documentation

MethodANNBase(const TString& jobName, TMVA::Types::EMVA methodType, const TString& methodTitle, TMVA::DataSetInfo& theData, const TString& theOption)
 constructors dictated by subclassing off of MethodBase
virtual ~MethodANNBase()
void InitANNBase()
 this does the real initialization work
void SetActivation(TMVA::TActivation* activation)
 setters for subclasses
void SetNeuronInputCalculator(TMVA::TNeuronInput* inputCalculator)
void Train()
 this will have to be overridden by every subclass
void PrintNetwork() const
 print network, for debugging
void AddWeightsXMLTo(void* parent) const
 write weights to file
void ReadWeightsFromXML(void* wghtnode)
void ReadWeightsFromStream(istream& istr)
 read weights from file
Double_t GetMvaValue(Double_t* err = 0, Double_t* errUpper = 0)
 calculate the MVA value
const std::vector<Float_t> & GetRegressionValues()
const std::vector<Float_t> & GetMulticlassValues()
void WriteMonitoringHistosToFile() const
 write method specific histos to target file
const Ranking* CreateRanking()
 ranking of input variables
void DeclareOptions()
 the option handling methods
void ProcessOptions()
Bool_t Debug() const
void MakeClassSpecific(ostream& , const TString& ) const
std::vector<Int_t>* ParseLayoutString(TString layerSpec)
void BuildNetwork(vector<Int_t>* layout, vector<Double_t>* weights = __null, Bool_t fromFile = kFALSE)
Double_t GetNetworkOutput()
{ return GetOutputNeuron()->GetActivationValue(); }
void PrintMessage(TString message, Bool_t force = kFALSE) const
 debugging utilities
void ForceNetworkCalculations()
void WaitForKeyboard()
Int_t NumCycles()
 accessors
{ return fNcycles; }
TNeuron* GetInputNeuron(Int_t index)
{ return (TNeuron*)fInputLayer->At(index); }
TNeuron* GetOutputNeuron(Int_t index = 0)
{ return fOutputNeurons.at(index); }
void CreateWeightMonitoringHists(const TString& bulkname, vector<TH1*>* hv = 0) const
 monitoring histograms (not available for regression)
void BuildLayers(vector<Int_t>* layout, Bool_t from_file = false)
 helper functions for building network
void BuildLayer(Int_t numNeurons, TObjArray* curLayer, TObjArray* prevLayer, Int_t layerIndex, Int_t numLayers, Bool_t from_file = false)
void InitWeights()
 helper functions for weight initialization
void ForceWeights(vector<Double_t>* weights)
void DeleteNetwork()
 helper functions for deleting network
void DeleteNetworkLayer(TObjArray*& layer)
void PrintLayer(TObjArray* layer) const
 debugging utilities
void PrintNeuron(TMVA::TNeuron* neuron) const