Virtual base Class for all MVA method MethodBase hosts several specific evaluation methods. The kind of MVA that provides optimal performance in an analysis strongly depends on the particular application. The evaluation factory provides a number of numerical benchmark results to directly assess the performance of the MVA training on the independent test sample. These are:
virtual | ~MethodBase() |
void | TObject::AbstractMethod(const char* method) const |
void | TObject::AbstractMethod(const char* method) const |
virtual void | AddClassifierToTestTree(TTree* theTestTree) |
virtual void | TObject::AppendPad(Option_t* option = "") |
virtual void | TObject::AppendPad(Option_t* option = "") |
TDirectory* | BaseDir() const |
virtual void | TObject::Browse(TBrowser* b) |
virtual void | TObject::Browse(TBrowser* b) |
void | TMVA::Configurable::CheckForUnusedOptions() const |
static TClass* | Class() |
virtual const char* | TObject::ClassName() const |
virtual const char* | TObject::ClassName() const |
virtual void | TObject::Clear(Option_t* = "") |
virtual void | TObject::Clear(Option_t* = "") |
virtual TObject* | TObject::Clone(const char* newname = "") const |
virtual TObject* | TObject::Clone(const char* newname = "") const |
virtual Int_t | TObject::Compare(const TObject* obj) 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 void | TObject::Copy(TObject& object) const |
virtual const TMVA::Ranking* | CreateRanking() |
TMVA::DataSet& | Data() const |
virtual void | TObject::Delete(Option_t* option = "")MENU |
virtual void | TObject::Delete(Option_t* option = "")MENU |
virtual Int_t | TObject::DistancetoPrimitive(Int_t px, Int_t py) |
virtual Int_t | TObject::DistancetoPrimitive(Int_t px, Int_t py) |
virtual void | TObject::Draw(Option_t* option = "") |
virtual void | TObject::Draw(Option_t* option = "") |
virtual void | TObject::DrawClass() constMENU |
virtual void | TObject::DrawClass() constMENU |
virtual TObject* | TObject::DrawClone(Option_t* option = "") constMENU |
virtual TObject* | TObject::DrawClone(Option_t* option = "") constMENU |
virtual void | TObject::Dump() constMENU |
virtual void | TObject::Dump() constMENU |
virtual void | TObject::Error(const char* method, const char* msgfmt) const |
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::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::ExecuteEvent(Int_t event, Int_t px, Int_t py) |
virtual void | TObject::Fatal(const char* method, const char* msgfmt) const |
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 |
virtual TObject* | TObject::FindObject(const char* name) const |
virtual TObject* | TObject::FindObject(const TObject* obj) const |
virtual Option_t* | TObject::GetDrawOption() const |
virtual Option_t* | TObject::GetDrawOption() const |
static Long_t | TObject::GetDtorOnly() |
static Long_t | TObject::GetDtorOnly() |
virtual Double_t | GetEfficiency(TString, TTree*, Double_t& err) |
TMVA::Event& | GetEvent() const |
Double_t | GetEventVal(Int_t ivar) const |
Double_t | GetEventValNormalised(Int_t ivar) const |
Double_t | GetEventWeight() const |
virtual const char* | TObject::GetIconName() const |
virtual const char* | TObject::GetIconName() const |
const TString& | GetInputExp(int i) const |
const TString& | GetInputVar(int i) const |
const TString& | GetJobName() const |
virtual Double_t | GetMaximumSignificance(Double_t SignalEvents, Double_t BackgroundEvents, Double_t& optimal_significance_value) const |
const TString& | GetMethodName() const |
const TString& | GetMethodTitle() const |
TMVA::Types::EMVA | GetMethodType() const |
virtual Double_t | GetMvaValue() |
virtual const char* | GetName() const |
Int_t | GetNvar() const |
virtual char* | TObject::GetObjectInfo(Int_t px, Int_t py) const |
virtual char* | TObject::GetObjectInfo(Int_t px, Int_t py) const |
static Bool_t | TObject::GetObjectStat() |
static Bool_t | TObject::GetObjectStat() |
virtual Option_t* | TObject::GetOption() const |
virtual Option_t* | TObject::GetOption() const |
const TString& | TMVA::Configurable::GetOptions() const |
virtual Double_t | GetProba(Double_t mvaVal, Double_t ap_sig) |
const TString | GetProbaName() const |
virtual Double_t | GetRarity(Double_t mvaVal, TMVA::Types::ESBType reftype = Types::kBackground) const |
Double_t | GetRMS(Int_t ivar) const |
virtual Double_t | GetSeparation(TH1*, TH1*) const |
virtual Double_t | GetSeparation(TMVA::PDF* pdfS = 0, TMVA::PDF* pdfB = 0) const |
Double_t | GetSignalReferenceCut() const |
virtual Double_t | GetSignificance() const |
const TString& | GetTestvarName() const |
virtual const char* | TObject::GetTitle() const |
virtual const char* | TObject::GetTitle() const |
virtual Double_t | GetTrainingEfficiency(TString) |
UInt_t | GetTrainingROOTVersionCode() const |
TString | GetTrainingROOTVersionString() const |
UInt_t | GetTrainingTMVAVersionCode() const |
TString | GetTrainingTMVAVersionString() const |
virtual UInt_t | TObject::GetUniqueID() const |
virtual UInt_t | TObject::GetUniqueID() const |
TMVA::VariableTransformBase& | GetVarTransform() const |
Double_t | GetXmax(Int_t ivar) const |
Double_t | GetXmin(Int_t ivar) const |
virtual Bool_t | TObject::HandleTimer(TTimer* timer) |
virtual Bool_t | TObject::HandleTimer(TTimer* timer) |
virtual ULong_t | TObject::Hash() const |
virtual ULong_t | TObject::Hash() const |
virtual void | TObject::Info(const char* method, const char* msgfmt) 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 Bool_t | TObject::InheritsFrom(const char* classname) const |
virtual Bool_t | TObject::InheritsFrom(const TClass* cl) const |
virtual void | TObject::Inspect() constMENU |
virtual void | TObject::Inspect() constMENU |
void | TObject::InvertBit(UInt_t f) |
void | TObject::InvertBit(UInt_t f) |
virtual TClass* | IsA() const |
virtual Bool_t | TObject::IsEqual(const TObject* obj) const |
virtual Bool_t | TObject::IsEqual(const TObject* obj) const |
virtual Bool_t | TObject::IsFolder() const |
virtual Bool_t | TObject::IsFolder() const |
Bool_t | TObject::IsOnHeap() const |
Bool_t | TObject::IsOnHeap() const |
Bool_t | IsSignalEvent() const |
virtual Bool_t | IsSignalLike() |
virtual Bool_t | TObject::IsSortable() const |
virtual Bool_t | TObject::IsSortable() const |
Bool_t | TObject::IsZombie() const |
Bool_t | TObject::IsZombie() const |
virtual void | TObject::ls(Option_t* option = "") const |
virtual void | TObject::ls(Option_t* option = "") const |
virtual void | MakeClass(const TString& classFileName = "") const |
void | TObject::MayNotUse(const char* method) const |
void | TObject::MayNotUse(const char* method) const |
TDirectory* | MethodBaseDir() const |
virtual Bool_t | TObject::Notify() |
virtual Bool_t | TObject::Notify() |
static void | TObject::operator delete(void* ptr) |
static void | TObject::operator delete(void* ptr) |
static void | TObject::operator delete(void* ptr, void* vp) |
static void | TObject::operator delete(void* ptr, void* vp) |
static void | TObject::operator delete[](void* ptr) |
static void | TObject::operator delete[](void* ptr) |
static void | TObject::operator delete[](void* ptr, void* vp) |
static void | TObject::operator delete[](void* ptr, void* vp) |
void* | TObject::operator new(size_t sz) |
void* | TObject::operator new(size_t sz) |
void* | TObject::operator new(size_t sz, void* vp) |
void* | TObject::operator new(size_t sz, void* vp) |
void* | TObject::operator new[](size_t sz) |
void* | TObject::operator new[](size_t sz) |
void* | TObject::operator new[](size_t sz, void* vp) |
void* | TObject::operator new[](size_t sz, void* vp) |
TMVA::IMethod& | TMVA::IMethod::operator=(const TMVA::IMethod&) |
virtual void | TObject::Paint(Option_t* option = "") |
virtual void | TObject::Paint(Option_t* option = "") |
void | TMVA::Configurable::ParseOptions(Bool_t verbose = kTRUE) |
virtual void | TObject::Pop() |
virtual void | TObject::Pop() |
virtual void | TObject::Print(Option_t* option = "") const |
virtual void | TObject::Print(Option_t* option = "") const |
virtual void | PrintHelpMessage() const |
void | TMVA::Configurable::PrintOptions() const |
virtual Int_t | TObject::Read(const char* name) |
virtual Int_t | TObject::Read(const char* name) |
Bool_t | ReadEvent(TTree* tr, UInt_t ievt, TMVA::Types::ESBType type = Types::kMaxSBType) const |
void | ReadStateFromFile() |
void | ReadStateFromStream(istream& tf) |
void | ReadStateFromStream(TFile& rf) |
Bool_t | ReadTestEvent(UInt_t ievt, TMVA::Types::ESBType type = Types::kMaxSBType) const |
Bool_t | ReadTrainingEvent(UInt_t ievt, TMVA::Types::ESBType type = Types::kMaxSBType) const |
virtual void | ReadWeightsFromStream(istream& tf) |
virtual void | ReadWeightsFromStream(TFile&) |
virtual void | TObject::RecursiveRemove(TObject* obj) |
virtual void | TObject::RecursiveRemove(TObject* obj) |
void | TObject::ResetBit(UInt_t f) |
void | TObject::ResetBit(UInt_t f) |
virtual void | TObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU |
virtual void | TObject::SaveAs(const char* filename = "", Option_t* option = "") constMENU |
virtual void | TObject::SavePrimitive(basic_ostream<char,char_traits<char> >& out, Option_t* option = "") |
virtual void | TObject::SavePrimitive(basic_ostream<char,char_traits<char> >& out, Option_t* option = "") |
void | TObject::SetBit(UInt_t f) |
void | TObject::SetBit(UInt_t f) |
void | TObject::SetBit(UInt_t f, Bool_t set) |
void | TObject::SetBit(UInt_t f, Bool_t set) |
virtual void | TObject::SetDrawOption(Option_t* option = "")MENU |
virtual void | TObject::SetDrawOption(Option_t* option = "")MENU |
static void | TObject::SetDtorOnly(void* obj) |
static void | TObject::SetDtorOnly(void* obj) |
void | SetMethodName(TString methodName) |
void | SetMethodTitle(TString methodTitle) |
void | SetMethodType(TMVA::Types::EMVA methodType) |
void | TMVA::Configurable::SetName(const char* n) |
static void | TObject::SetObjectStat(Bool_t stat) |
static void | TObject::SetObjectStat(Bool_t stat) |
void | TMVA::Configurable::SetOptions(const TString& s) |
void | SetTestvarName(const TString& v = "") |
void | SetTestvarPrefix(TString prefix) |
virtual void | TObject::SetUniqueID(UInt_t uid) |
virtual void | TObject::SetUniqueID(UInt_t uid) |
virtual void | ShowMembers(TMemberInspector& insp, char* parent) |
virtual void | Streamer(TBuffer& b) |
void | StreamerNVirtual(TBuffer& b) |
virtual void | TObject::SysError(const char* method, const char* msgfmt) const |
virtual void | TObject::SysError(const char* method, const char* msgfmt) const |
virtual void | Test(TTree* theTestTree = 0) |
Bool_t | TObject::TestBit(UInt_t f) const |
Bool_t | TObject::TestBit(UInt_t f) const |
Int_t | TObject::TestBits(UInt_t f) const |
Int_t | TObject::TestBits(UInt_t f) const |
virtual void | Train() |
void | TrainMethod() |
virtual void | TObject::UseCurrentStyle() |
virtual void | TObject::UseCurrentStyle() |
virtual void | TObject::Warning(const char* method, const char* msgfmt) const |
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 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 | WriteEvaluationHistosToFile() |
virtual void | WriteMonitoringHistosToFile() const |
void | WriteStateToFile() const |
void | WriteStateToStream(TFile& rf) const |
void | WriteStateToStream(ostream& tf, Bool_t isClass = kFALSE) const |
virtual void | WriteWeightsToStream(ostream& tf) const |
virtual void | WriteWeightsToStream(TFile&) const |
void | CreateMVAPdfs() |
TMVA::MethodBase::ECutOrientation | GetCutOrientation() const |
Double_t | GetEffForRoot(Double_t) |
Bool_t | GetLine(istream& fin, char* buf) |
Bool_t | HasMVAPdfs() const |
static Double_t | IGetEffForRoot(Double_t) |
void | Init() |
void | ResetThisBase() |
enum EWeightFileType { | kROOT | |
kTEXT | ||
}; | ||
enum ECutOrientation { | kNegative | |
kPositive | ||
}; | ||
enum TObject::EStatusBits { | kCanDelete | |
kMustCleanup | ||
kObjInCanvas | ||
kIsReferenced | ||
kHasUUID | ||
kCannotPick | ||
kNoContextMenu | ||
kInvalidObject | ||
}; | ||
enum TObject::[unnamed] { | kIsOnHeap | |
kNotDeleted | ||
kZombie | ||
kBitMask | ||
kSingleKey | ||
kOverwrite | ||
kWriteDelete | ||
}; | ||
enum TObject::EStatusBits { | kCanDelete | |
kMustCleanup | ||
kObjInCanvas | ||
kIsReferenced | ||
kHasUUID | ||
kCannotPick | ||
kNoContextMenu | ||
kInvalidObject | ||
}; | ||
enum TObject::[unnamed] { | kIsOnHeap | |
kNotDeleted | ||
kZombie | ||
kBitMask | ||
kSingleKey | ||
kOverwrite | ||
kWriteDelete | ||
}; |
TMVA::MsgLogger | TMVA::Configurable::fLogger | message logger |
vector<TString>* | fInputVars | vector of input variables used in MVA |
TMVA::MsgLogger | fLogger | message logger |
Int_t | fNbins | number of bins in representative histograms |
Int_t | fNbinsH | number of bins in evaluation histograms |
TMVA::Ranking* | fRanking | pointer to ranking object (created by derived classifiers) |
TDirectory* | fBaseDir | base directory for the instance, needed to know where to jump back from localDir |
TMVA::MethodBase::ECutOrientation | fCutOrientation | +1 if Sig>Bkg, -1 otherwise |
TMVA::DataSet& | fData | ! the data set |
TH1* | fEffB | efficiency plot (background) |
TH1* | fEffBvsS | background efficiency versus signal efficiency |
TH1* | fEffS | efficiency plot (signal) |
TString | fFileDir | unix sub-directory for weight files (default: "weights") |
TGraph* | fGraphB | graphs used for splines for efficiency (background) |
TGraph* | fGraphS | graphs used for splines for efficiency (signal) |
TGraph* | fGraphTrainB | graphs used for splines for training efficiency (background) |
TGraph* | fGraphTrainEffBvsS | graphs used for splines for training signal eff. versus background eff. |
TGraph* | fGraphTrainS | graphs used for splines for training efficiency (signal) |
TGraph* | fGrapheffBvsS | graphs used for splines for signal eff. versus background eff. |
Bool_t | fHasMVAPdfs | MVA Pdfs are created for this classifier |
Bool_t | fHelp | help flag |
TH1* | fHistB_highbin | MVA plots used for efficiency calculations (background) |
TH1* | fHistB_plotbin | MVA plots used for graphics representation (background) |
TH1* | fHistS_highbin | MVA plots used for efficiency calculations (signal) |
TH1* | fHistS_plotbin | MVA plots used for graphics representation (signal) |
TH1* | fHistTrB_plotbin | same plots as above for training sample (check for overtraining) |
TH1* | fHistTrS_plotbin | same plots as above for training sample (check for overtraining) |
TString | fJobName | name of job -> user defined, appears in weight files |
TMVA::PDF* | fMVAPdfB | background MVA PDF |
TMVA::PDF* | fMVAPdfS | signal MVA PDF |
Double_t | fMeanB | mean (background) |
Double_t | fMeanS | mean (signal) |
TDirectory* | fMethodBaseDir | base directory for the method |
TString | fMethodName | name of the method (set in derived class) |
TString | fMethodTitle | user-defined title for method (used for weight-file names) |
TMVA::Types::EMVA | fMethodType | type of method (set in derived class) |
Int_t | fNbinsMVAPdf | number of bins used in histogram that creates PDF |
Bool_t | fNormalise | normalise input variables |
Int_t | fNsmoothMVAPdf | number of times a histogram is smoothed before creating the PDF |
Int_t | fNvar | number of input variables |
TH1* | fProbaB_plotbin | P(MVA) plots used for graphics representation (background) |
TH1* | fProbaS_plotbin | P(MVA) plots used for graphics representation (signal) |
UInt_t | fROOTTrainingVersion | ROOT version used for training |
TH1* | fRarityB_plotbin | R(MVA) plots used for graphics representation (background) |
TH1* | fRarityS_plotbin | R(MVA) plots used for graphics representation (signal) |
TH1* | fRejBvsS | background rejection (=1-eff.) versus signal efficiency |
Double_t | fRmsB | RMS (background) |
Double_t | fRmsS | RMS (signal) |
Double_t | fSignalReferenceCut | minimum requirement on the MVA output to declare an event signal-like |
TMVA::PDF* | fSplB | PDFs of MVA distribution (background) |
TMVA::TSpline1* | fSplRefB | helper splines for RootFinder (background) |
TMVA::TSpline1* | fSplRefS | helper splines for RootFinder (signal) |
TMVA::PDF* | fSplS | PDFs of MVA distribution (signal) |
TMVA::PDF* | fSplTrainB | PDFs of training MVA distribution (background) |
TSpline* | fSplTrainEffBvsS | splines for training signal eff. versus background eff. |
TMVA::TSpline1* | fSplTrainRefB | helper splines for RootFinder (background) |
TMVA::TSpline1* | fSplTrainRefS | helper splines for RootFinder (signal) |
TMVA::PDF* | fSplTrainS | PDFs of training MVA distribution (signal) |
TSpline* | fSpleffBvsS | splines for signal eff. versus background eff. |
UInt_t | fTMVATrainingVersion | TMVA version used for training |
TString | fTestvar | variable used in evaluation, etc (mostly the MVA) |
TString | fTestvarPrefix | 'MVA_' prefix of MVA variable |
TH1* | fTrainEffB | Training efficiency plot (background) |
TH1* | fTrainEffBvsS | Training background efficiency versus signal efficiency |
TH1* | fTrainEffS | Training efficiency plot (signal) |
TH1* | fTrainRejBvsS | Training background rejection (=1-eff.) versus signal efficiency |
Bool_t | fTxtWeightsOnly | if TRUE, write weights only to text files |
Bool_t | fUseDecorr | kept for backward compatibility |
TMVA::VariableTransformBase* | fVarTransform | the variable transformer |
TString | fVarTransformString | labels variable transform method |
TMVA::Types::EVariableTransform | fVariableTransform | Decorrelation, PCA, etc. |
TMVA::Types::ESBType | fVariableTransformType | this is the event type (sig or bgd) assumed for variable transform |
TString | fVariableTransformTypeString | labels variable transform type |
Bool_t | fVerbose | verbose flag |
TMVA::EMsgType | fVerbosityLevel | verbosity level |
TString | fVerbosityLevelString | verbosity level (user input string) |
TString | fWeightFile | weight file name |
Double_t | fXmax | maximum (signal and background) |
Double_t | fXmin | minimum (signal and background) |
static TMVA::MethodBase* | fgThisBase | this pointer |
TH1* | finvBeffvsSeff | inverse background eff (1/eff.) versus signal efficiency |
define the options (their key words) that can be set in the option string here the options valid for ALL MVA methods are declared. know options: VariableTransform=None,Decorrelated,PCA to use transformed variables instead of the original ones VariableTransformType=Signal,Background which decorrelation matrix to use in the method. Only the Likelihood Method can make proper use of independent transformations of signal and background fNbinsMVAPdf = 50 Number of bins used to create a PDF of MVA fNsmoothMVAPdf = 2 Number of times a histogram is smoothed before creating the PDF fHasMVAPdfs create PDFs for the MVA outputs V for Verbose output (!V) for non verbos H for Help message
prepare tree branch with the method's discriminating variable
test the method - not much is done here... mainly further initialization
general method used in writing the header of the weight files where the used variables, variable transformation type etc. is specified
write reference MVA distributions (and other information) to a ROOT type weight file
write reference MVA distributions (and other information) to a ROOT type weight file
read the header from the weight files of the different MVA methods
returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored
returns the ROOT directory where all instances of the corresponding MVA method are stored
write special monitoring histograms to file - not implemented for this method
reads one line from the input stream checks for certain keywords and interprets the line if keywords are found
compute rarity: R(x) = Integrate_[-oo..x] { PDF(x') dx' } where PDF(x) is the PDF of the classifier's signal or background distribution
fill background efficiency (resp. rejection) versus signal efficiency plots returns signal efficiency at background efficiency indicated in theString
fill background efficiency (resp. rejection) versus signal efficiency plots returns signal efficiency at background efficiency indicated in theString
compute significance of mean difference significance = |<S> - <B>|/Sqrt(RMS_S2 + RMS_B2)
compute "separation" defined as
<s2> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx }
compute "separation" defined as
<s2> = (1/2) Int_-oo..+oo { (S(x)2 - B(x)2)/(S(x) + B(x)) dx }
plot significance, S/Sqrt(S^2 + B^2), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance
calculates rms,mean, xmin, xmax of the event variable this can be either done for the variables as they are or for normalised variables (in the range of 0-1) if "norm" is set to kTRUE
---------- public accessors ----------------------------------------------- classifier naming (a lot of names ... aren't they ;-)
{ return fJobName; }
build classifier name in Test tree MVA prefix (e.g., "TMVA_")
{ fTestvarPrefix = prefix; }
{ fTestvar = (v=="")?(fTestvarPrefix + GetMethodTitle()):v; }
internal names and expressions of input variables
{ return Data().GetInternalVarName(i); }
normalisation and limit accessors
{ return GetVarTransform().Variable(ivar).GetRMS(); }
sets the minimum requirement on the MVA output to declare an event signal-like
{ return fSignalReferenceCut; }
the TMVA versions can be checked using if (GetTrainingTMVAVersionCode()>TMVA_VERSION(3,7,2)) {...} or if (GetTrainingROOTVersionCode()>ROOT_VERSION(5,15,5)) {...}
{ return fTMVATrainingVersion; }
---------- public auxiliary methods ---------------------------------------
this method is used to decide whether an event is signal- or background-like
the reference cut "xC" is taken to be where
Int_[-oo,xC] { PDF_S(x) dx } = Int_[xC,+oo] { PDF_B(x) dx }
{ return GetMvaValue() > GetSignalReferenceCut() ? kTRUE : kFALSE; }
---------- protected acccessors -------------------------------------------
{ return Data().LocalRootDir(); }
set number of input variables (only used by MethodCuts, could perhaps be removed)
{ fNvar = n; }
the type of the variable transformation required for the data set of this classifier
{ return fVariableTransform; }
sets the minimum requirement on the MVA output to declare an event signal-like
{ fSignalReferenceCut = cut; }
---------- protected event and tree accessors ----------------------------- names of input variables (if the original names are expressions, they are transformed into regexps)
{ return (*fInputVars)[ivar]; }
accessing training and test trees
{ return Data().GetTrainingTree() != 0; }
make ROOT-independent C++ class for classifier response (classifier-specific implementation)
{}
static pointer to this object - required for ROOT finder (to be solved differently)
{ return fgThisBase; }
---------- private acccessors --------------------------------------------- reset required for RootFinder
{ fgThisBase = this; }