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Reference Guide
TMVA::MethodBase Class Referenceabstract

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:

  • The signal efficiency at three representative background efficiencies (which is 1 − rejection).
  • The significance of an MVA estimator, defined by the difference between the MVA mean values for signal and background, divided by the quadratic sum of their root mean squares.
  • The separation of an MVA x, defined by the integral

    \[ \frac{1}{2} \int \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx \]

    where \( S(x) \) and \( B(x) \) are the signal and background distributions, respectively. The separation is zero for identical signal and background MVA shapes, and it is one for disjunctive shapes.
  • The average, \( \int x \mu (S(x)) dx \), of the signal \( \mu_{transform} \). The \( \mu_{transform} \) of an MVA denotes the transformation that yields a uniform background distribution. In this way, the signal distributions \( S(x) \) can be directly compared among the various MVAs. The stronger \( S(x) \) peaks towards one, the better is the discrimination of the MVA. The \( \mu_{transform} \) is documented here.

    The MVA standard output also prints the linear correlation coefficients between signal and background, which can be useful to eliminate variables that exhibit too strong correlations.

Definition at line 111 of file MethodBase.h.

Public Types

enum  EWeightFileType { kROOT =0, kTEXT }
 
- Public Types inherited from TObject
enum  {
  kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kInconsistent = 0x08000000,
  kBitMask = 0x00ffffff
}
 
enum  { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = BIT(3) }
 
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5),
  kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 

Public Member Functions

 MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="")
 standard constructor More...
 
 MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile)
 constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles More...
 
virtual ~MethodBase ()
 destructor More...
 
void AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType)
 
TDirectoryBaseDir () const
 returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored More...
 
virtual void CheckSetup ()
 check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
virtual const RankingCreateRanking ()=0
 
DataSetData () const
 
DataSetInfoDataInfo () const
 
virtual void DeclareCompatibilityOptions ()
 options that are used ONLY for the READER to ensure backward compatibility they are hence without any effect (the reader is only reading the training options that HAD been used at the training of the .xml weight file at hand More...
 
virtual void DeclareOptions ()=0
 
void DisableWriting (Bool_t setter)
 
Bool_t DoMulticlass () const
 
Bool_t DoRegression () const
 
void ExitFromTraining ()
 
Types::EAnalysisType GetAnalysisType () const
 
UInt_t GetCurrentIter ()
 
virtual Double_t GetEfficiency (const TString &, Types::ETreeType, Double_t &err)
 fill background efficiency (resp. More...
 
const EventGetEvent () const
 
const EventGetEvent (const TMVA::Event *ev) const
 
const EventGetEvent (Long64_t ievt) const
 
const EventGetEvent (Long64_t ievt, Types::ETreeType type) const
 
const std::vector< TMVA::Event * > & GetEventCollection (Types::ETreeType type)
 returns the event collection (i.e. More...
 
TFileGetFile () const
 
const TStringGetInputLabel (Int_t i) const
 
const char * GetInputTitle (Int_t i) const
 
const TStringGetInputVar (Int_t i) const
 
TMultiGraphGetInteractiveTrainingError ()
 
const TStringGetJobName () const
 
virtual Double_t GetKSTrainingVsTest (Char_t SorB, TString opt="X")
 
virtual Double_t GetMaximumSignificance (Double_t SignalEvents, Double_t BackgroundEvents, Double_t &optimal_significance_value) const
 plot significance, \( \frac{S}{\sqrt{S^2 + B^2}} \), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance More...
 
UInt_t GetMaxIter ()
 
Double_t GetMean (Int_t ivar) const
 
const TStringGetMethodName () const
 
Types::EMVA GetMethodType () const
 
TString GetMethodTypeName () const
 
virtual TMatrixD GetMulticlassConfusionMatrix (Double_t effB, Types::ETreeType type)
 Construct a confusion matrix for a multiclass classifier. More...
 
virtual std::vector< Float_tGetMulticlassEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual std::vector< Float_tGetMulticlassTrainingEfficiency (std::vector< std::vector< Float_t > > &purity)
 
virtual const std::vector< Float_t > & GetMulticlassValues ()
 
virtual Double_t GetMvaValue (Double_t *errLower=0, Double_t *errUpper=0)=0
 
Double_t GetMvaValue (const TMVA::Event *const ev, Double_t *err=0, Double_t *errUpper=0)
 
const char * GetName () const
 
UInt_t GetNEvents () const
 temporary event when testing on a different DataSet than the own one More...
 
UInt_t GetNTargets () const
 
UInt_t GetNvar () const
 
UInt_t GetNVariables () const
 
virtual Double_t GetProba (const Event *ev)
 
virtual Double_t GetProba (Double_t mvaVal, Double_t ap_sig)
 compute likelihood ratio More...
 
const TString GetProbaName () const
 
virtual Double_t GetRarity (Double_t mvaVal, Types::ESBType reftype=Types::kBackground) const
 compute rarity:

\[ R(x) = \int_{[-\infty..x]} { PDF(x') dx' } \]

where PDF(x) is the PDF of the classifier's signal or background distribution More...

 
virtual void GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const
 
const std::vector< Float_t > & GetRegressionValues (const TMVA::Event *const ev)
 
virtual const std::vector< Float_t > & GetRegressionValues ()
 
Double_t GetRMS (Int_t ivar) const
 
virtual Double_t GetROCIntegral (TH1D *histS, TH1D *histB) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetROCIntegral (PDF *pdfS=0, PDF *pdfB=0) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t GetSeparation (TH1 *, TH1 *) const
 compute "separation" defined as

\[ <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } \]

More...
 
virtual Double_t GetSeparation (PDF *pdfS=0, PDF *pdfB=0) const
 compute "separation" defined as

\[ <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } \]

More...
 
Double_t GetSignalReferenceCut () const
 
Double_t GetSignalReferenceCutOrientation () const
 
virtual Double_t GetSignificance () const
 compute significance of mean difference

\[ significance = \frac{|<S> - <B>|}{\sqrt{RMS_{S2} + RMS_{B2}}} \]

More...
 
const EventGetTestingEvent (Long64_t ievt) const
 
Double_t GetTestTime () const
 
const TStringGetTestvarName () const
 
virtual Double_t GetTrainingEfficiency (const TString &)
 
const EventGetTrainingEvent (Long64_t ievt) const
 
virtual const std::vector< Float_t > & GetTrainingHistory (const char *)
 
UInt_t GetTrainingROOTVersionCode () const
 
TString GetTrainingROOTVersionString () const
 calculates the ROOT version string from the training version code on the fly More...
 
UInt_t GetTrainingTMVAVersionCode () const
 
TString GetTrainingTMVAVersionString () const
 calculates the TMVA version string from the training version code on the fly More...
 
Double_t GetTrainTime () const
 
TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true)
 
const TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true) const
 
TString GetWeightFileName () const
 retrieve weight file name More...
 
Double_t GetXmax (Int_t ivar) const
 
Double_t GetXmin (Int_t ivar) const
 
Bool_t HasMVAPdfs () const
 
virtual void Init ()=0
 
void InitIPythonInteractive ()
 
Bool_t IsModelPersistence () const
 
virtual Bool_t IsSignalLike ()
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event would be selected as signal or background More...
 
virtual Bool_t IsSignalLike (Double_t mvaVal)
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event with this mva output value would be selected as signal or background More...
 
Bool_t IsSilentFile () const
 
virtual void MakeClass (const TString &classFileName=TString("")) const
 create reader class for method (classification only at present) More...
 
TDirectoryMethodBaseDir () const
 returns the ROOT directory where all instances of the corresponding MVA method are stored More...
 
virtual std::map< TString, Double_tOptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
 call the Optimizer with the set of parameters and ranges that are meant to be tuned. More...
 
void PrintHelpMessage () const
 prints out method-specific help method More...
 
virtual void ProcessOptions ()=0
 
void ProcessSetup ()
 process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
void ReadStateFromFile ()
 Function to write options and weights to file. More...
 
void ReadStateFromStream (std::istream &tf)
 read the header from the weight files of the different MVA methods More...
 
void ReadStateFromStream (TFile &rf)
 write reference MVA distributions (and other information) to a ROOT type weight file More...
 
void ReadStateFromXMLString (const char *xmlstr)
 for reading from memory More...
 
void RerouteTransformationHandler (TransformationHandler *fTargetTransformation)
 
virtual void Reset ()
 
virtual void SetAnalysisType (Types::EAnalysisType type)
 
void SetBaseDir (TDirectory *methodDir)
 
void SetFile (TFile *file)
 
void SetMethodBaseDir (TDirectory *methodDir)
 
void SetMethodDir (TDirectory *methodDir)
 
void SetModelPersistence (Bool_t status)
 
void SetSignalReferenceCut (Double_t cut)
 
void SetSignalReferenceCutOrientation (Double_t cutOrientation)
 
void SetSilentFile (Bool_t status)
 
void SetTestTime (Double_t testTime)
 
void SetTestvarName (const TString &v="")
 
void SetTrainTime (Double_t trainTime)
 
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
 set the tuning parameters according to the argument This is just a dummy . More...
 
void SetupMethod ()
 setup of methods More...
 
virtual void TestClassification ()
 initialization More...
 
virtual void TestMulticlass ()
 test multiclass classification More...
 
virtual void 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, Types::ETreeType type)
 calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample More...
 
virtual void Train ()=0
 
bool TrainingEnded ()
 
void TrainMethod ()
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file More...
 
virtual void WriteMonitoringHistosToFile () const
 write special monitoring histograms to file dummy implementation here --------------— More...
 
void WriteStateToFile () const
 write options and weights to file note that each one text file for the main configuration information and one ROOT file for ROOT objects are created More...
 
- Public Member Functions inherited from TMVA::IMethod
 IMethod ()
 
virtual ~IMethod ()
 
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)=0
 
- Public Member Functions inherited from TMVA::Configurable
 Configurable (const TString &theOption="")
 constructor More...
 
virtual ~Configurable ()
 default destructor More...
 
void AddOptionsXMLTo (void *parent) const
 write options to XML file More...
 
template<class T >
void AddPreDefVal (const T &)
 
template<class T >
void AddPreDefVal (const TString &optname, const T &)
 
void CheckForUnusedOptions () const
 checks for unused options in option string More...
 
template<class T >
OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc="")
 
template<class T >
OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")
 
template<class T >
TMVA::OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc)
 
template<class T >
TMVA::OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc)
 
const char * GetConfigDescription () const
 
const char * GetConfigName () const
 
const TStringGetOptions () const
 
MsgLoggerLog () const
 
virtual void ParseOptions ()
 options parser More...
 
void PrintOptions () const
 prints out the options set in the options string and the defaults More...
 
void ReadOptionsFromStream (std::istream &istr)
 read option back from the weight file More...
 
void ReadOptionsFromXML (void *node)
 
void SetConfigDescription (const char *d)
 
void SetConfigName (const char *n)
 
void SetMsgType (EMsgType t)
 
void SetOptions (const TString &s)
 
void WriteOptionsToStream (std::ostream &o, const TString &prefix) const
 write options to output stream (e.g. in writing the MVA weight files More...
 
- Public Member Functions inherited from TNamed
 TNamed ()
 
 TNamed (const char *name, const char *title)
 
 TNamed (const TString &name, const TString &title)
 
 TNamed (const TNamed &named)
 TNamed copy ctor. More...
 
virtual ~TNamed ()
 TNamed destructor. More...
 
virtual void Clear (Option_t *option="")
 Set name and title to empty strings (""). More...
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility. More...
 
virtual Int_t Compare (const TObject *obj) const
 Compare two TNamed objects. More...
 
virtual void Copy (TObject &named) const
 Copy this to obj. More...
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer. More...
 
virtual const char * GetTitle () const
 Returns title of object. More...
 
virtual ULong_t Hash () const
 Return hash value for this object. More...
 
virtual Bool_t IsSortable () const
 
virtual void ls (Option_t *option="") const
 List TNamed name and title. More...
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator. More...
 
virtual void Print (Option_t *option="") const
 Print TNamed name and title. More...
 
virtual void SetName (const char *name)
 Set the name of the TNamed. More...
 
virtual void SetNameTitle (const char *name, const char *title)
 Set all the TNamed parameters (name and title). More...
 
virtual void SetTitle (const char *title="")
 Set the title of the TNamed. More...
 
virtual Int_t Sizeof () const
 Return size of the TNamed part of the TObject. More...
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor. More...
 
 TObject (const TObject &object)
 TObject copy ctor. More...
 
virtual ~TObject ()
 TObject destructor. More...
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad. More...
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action. More...
 
ULong_t CheckedHash ()
 Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. More...
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs. More...
 
virtual void Delete (Option_t *option="")
 Delete this object. More...
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object. More...
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects. More...
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs. More...
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current selected pad for instance with: gROOT->SetSelectedPad(gPad). More...
 
virtual void Dump () const
 Dump contents of object on stdout. More...
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message. More...
 
virtual void Execute (const char *method, const char *params, Int_t *error=0)
 Execute method on this object with the given parameter string, e.g. More...
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=0)
 Execute method on this object with parameters stored in the TObjArray. More...
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py). More...
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message. More...
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes. More...
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes. More...
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object. More...
 
virtual const char * GetIconName () const
 Returns mime type name of object. More...
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py). More...
 
virtual Option_tGetOption () const
 
virtual UInt_t GetUniqueID () const
 Return the unique object id. More...
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out. More...
 
Bool_t HasInconsistentHash () const
 Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e. More...
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message. More...
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname". More...
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl. More...
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas. More...
 
void InvertBit (UInt_t f)
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory). More...
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...
 
R__ALWAYS_INLINE Bool_t IsOnHeap () const
 
R__ALWAYS_INLINE Bool_t IsZombie () const
 
void MayNotUse (const char *method) const
 Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification. More...
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete. More...
 
void operator delete (void *ptr)
 Operator delete. More...
 
void operator delete[] (void *ptr)
 Operator delete []. More...
 
voidoperator new (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz)
 
voidoperator new[] (size_t sz, void *vp)
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator. More...
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself. More...
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list. More...
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory. More...
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list. More...
 
void ResetBit (UInt_t f)
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename. More...
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out". More...
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f. More...
 
void SetBit (UInt_t f)
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object. More...
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id. More...
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message. More...
 
R__ALWAYS_INLINE Bool_t TestBit (UInt_t f) const
 
Int_t TestBits (UInt_t f) const
 
virtual void UseCurrentStyle ()
 Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory. More...
 

Public Attributes

Bool_t fSetupCompleted
 
const EventfTmpEvent
 
TrainingHistory fTrainHistory
 

Protected Member Functions

virtual void AddWeightsXMLTo (void *parent) const =0
 
const TStringGetInternalVarName (Int_t ivar) const
 
virtual std::vector< Double_tGetMvaValues (Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false)
 get all the MVA values for the events of the current Data type More...
 
const TStringGetOriginalVarName (Int_t ivar) const
 
const TStringGetWeightFileDir () const
 
Bool_t HasTrainingTree () const
 
Bool_t Help () const
 
Bool_t IgnoreEventsWithNegWeightsInTraining () const
 
Bool_t IsConstructedFromWeightFile () const
 
Bool_t IsNormalised () const
 
virtual void MakeClassSpecific (std::ostream &, const TString &="") const
 
virtual void MakeClassSpecificHeader (std::ostream &, const TString &="") const
 
void NoErrorCalc (Double_t *const err, Double_t *const errUpper)
 
virtual void ReadWeightsFromStream (std::istream &)=0
 
virtual void ReadWeightsFromStream (TFile &)
 
virtual void ReadWeightsFromXML (void *wghtnode)=0
 
void SetNormalised (Bool_t norm)
 
void SetWeightFileDir (TString fileDir)
 set directory of weight file More...
 
void SetWeightFileName (TString)
 set the weight file name (depreciated) More...
 
void Statistics (Types::ETreeType treeType, const TString &theVarName, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &, Double_t &)
 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 More...
 
Bool_t TxtWeightsOnly () const
 
Bool_t Verbose () const
 
- Protected Member Functions inherited from TMVA::IMethod
virtual void GetHelpMessage () const =0
 
- Protected Member Functions inherited from TMVA::Configurable
void EnableLooseOptions (Bool_t b=kTRUE)
 
const TStringGetReferenceFile () const
 
Bool_t LooseOptionCheckingEnabled () const
 
void ResetSetFlag ()
 resets the IsSet flag for all declare options to be called before options are read from stream More...
 
void WriteOptionsReferenceToFile ()
 write complete options to output stream More...
 
- Protected Member Functions inherited from TObject
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected). More...
 
void MakeZombie ()
 

Protected Attributes

Types::EAnalysisType fAnalysisType
 
UInt_t fBackgroundClass
 
bool fExitFromTraining = false
 
std::vector< TString > * fInputVars
 
IPythonInteractivefInteractive = nullptr
 
UInt_t fIPyCurrentIter = 0
 
UInt_t fIPyMaxIter = 0
 
std::vector< Float_t > * fMulticlassReturnVal
 
Int_t fNbins
 
Int_t fNbinsH
 
Int_t fNbinsMVAoutput
 
RankingfRanking
 
std::vector< Float_t > * fRegressionReturnVal
 
ResultsfResults
 
UInt_t fSignalClass
 
- Protected Attributes inherited from TMVA::Configurable
MsgLoggerfLogger
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

Private Types

enum  ECutOrientation { kNegative = -1, kPositive = +1 }
 

Private Member Functions

void AddClassesXMLTo (void *parent) const
 write class info to XML More...
 
virtual void AddClassifierOutput (Types::ETreeType type)
 prepare tree branch with the method's discriminating variable More...
 
virtual void AddClassifierOutputProb (Types::ETreeType type)
 prepare tree branch with the method's discriminating variable More...
 
void AddInfoItem (void *gi, const TString &name, const TString &value) const
 xml writing More...
 
virtual void AddMulticlassOutput (Types::ETreeType type)
 prepare tree branch with the method's discriminating variable More...
 
virtual void AddRegressionOutput (Types::ETreeType type)
 prepare tree branch with the method's discriminating variable More...
 
void AddSpectatorsXMLTo (void *parent) const
 write spectator info to XML More...
 
void AddTargetsXMLTo (void *parent) const
 write target info to XML More...
 
void AddVarsXMLTo (void *parent) const
 write variable info to XML More...
 
void CreateMVAPdfs ()
 Create PDFs of the MVA output variables. More...
 
void DeclareBaseOptions ()
 define the options (their key words) that can be set in the option string here the options valid for ALL MVA methods are declared. More...
 
ECutOrientation GetCutOrientation () const
 
Bool_t GetLine (std::istream &fin, char *buf)
 reads one line from the input stream checks for certain keywords and interprets the line if keywords are found More...
 
virtual Double_t GetValueForRoot (Double_t)
 returns efficiency as function of cut More...
 
void InitBase ()
 default initialization called by all constructors More...
 
void ProcessBaseOptions ()
 the option string is decoded, for available options see "DeclareOptions" More...
 
void ReadClassesFromXML (void *clsnode)
 read number of classes from XML More...
 
void ReadSpectatorsFromXML (void *specnode)
 read spectator info from XML More...
 
void ReadStateFromXML (void *parent)
 
void ReadTargetsFromXML (void *tarnode)
 read target info from XML More...
 
void ReadVariablesFromXML (void *varnode)
 read variable info from XML More...
 
void ReadVarsFromStream (std::istream &istr)
 Read the variables (name, min, max) for a given data transformation method from the stream. More...
 
void ResetThisBase ()
 
void WriteStateToStream (std::ostream &tf) const
 general method used in writing the header of the weight files where the used variables, variable transformation type etc. More...
 
void WriteStateToXML (void *parent) const
 general method used in writing the header of the weight files where the used variables, variable transformation type etc. More...
 
void WriteVarsToStream (std::ostream &tf, const TString &prefix="") const
 write the list of variables (name, min, max) for a given data transformation method to the stream More...
 

Private Attributes

TDirectoryfBaseDir
 
Bool_t fConstructedFromWeightFile
 
ECutOrientation fCutOrientation
 
DataSetInfofDataSetInfo
 
PDFfDefaultPDF
 
TH1fEffS
 
std::vector< const std::vector< TMVA::Event * > * > fEventCollections
 
TFilefFile
 
TString fFileDir
 
Bool_t fHasMVAPdfs
 
Bool_t fHelp
 
Bool_t fIgnoreNegWeightsInTraining
 
TString fJobName
 
Double_t fMeanB
 
Double_t fMeanS
 
TDirectoryfMethodBaseDir
 
TString fMethodName
 
Types::EMVA fMethodType
 
Bool_t fModelPersistence
 
PDFfMVAPdfB
 
PDFfMVAPdfS
 
Int_t fNbinsMVAPdf
 
Bool_t fNormalise
 
Int_t fNsmoothMVAPdf
 
TString fParentDir
 
Double_t fRmsB
 
Double_t fRmsS
 
UInt_t fROOTTrainingVersion
 
Double_t fSignalReferenceCut
 the data set information (sometimes needed) More...
 
Double_t fSignalReferenceCutOrientation
 
Bool_t fSilentFile
 
PDFfSplB
 
TSplinefSpleffBvsS
 
TSpline1fSplRefB
 
TSpline1fSplRefS
 
PDFfSplS
 
PDFfSplTrainB
 
TSplinefSplTrainEffBvsS
 
TSpline1fSplTrainRefB
 
TSpline1fSplTrainRefS
 
PDFfSplTrainS
 
Double_t fTestTime
 
TString fTestvar
 
UInt_t fTMVATrainingVersion
 
Double_t fTrainTime
 
TransformationHandler fTransformation
 
TransformationHandlerfTransformationPointer
 
Bool_t fTxtWeightsOnly
 
Bool_t fUseDecorr
 
Types::ESBType fVariableTransformType
 
TString fVariableTransformTypeString
 
TString fVarTransformString
 
Bool_t fVerbose
 
EMsgType fVerbosityLevel
 
TString fVerbosityLevelString
 
TString fWeightFile
 
Double_t fXmax
 
Double_t fXmin
 

Friends

class CrossValidation
 
class Experimental::Classification
 
class Factory
 
class MethodBoost
 
class MethodCategory
 
class MethodCompositeBase
 
class MethodCrossValidation
 
class MethodCuts
 
class RootFinder
 

Additional Inherited Members

- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 

#include <TMVA/MethodBase.h>

Inheritance diagram for TMVA::MethodBase:
[legend]

Member Enumeration Documentation

◆ ECutOrientation

enum TMVA::MethodBase::ECutOrientation
private
Enumerator
kNegative 
kPositive 

Definition at line 549 of file MethodBase.h.

◆ EWeightFileType

enum TMVA::MethodBase::EWeightFileType
Enumerator
kROOT 
kTEXT 

Definition at line 122 of file MethodBase.h.

Constructor & Destructor Documentation

◆ MethodBase() [1/2]

TMVA::MethodBase::MethodBase ( const TString jobName,
Types::EMVA  methodType,
const TString methodTitle,
DataSetInfo dsi,
const TString theOption = "" 
)

standard constructor

Definition at line 237 of file MethodBase.cxx.

◆ MethodBase() [2/2]

TMVA::MethodBase::MethodBase ( Types::EMVA  methodType,
DataSetInfo dsi,
const TString weightFile 
)

constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles

Definition at line 303 of file MethodBase.cxx.

◆ ~MethodBase()

TMVA::MethodBase::~MethodBase ( void  )
virtual

destructor

Definition at line 364 of file MethodBase.cxx.

Member Function Documentation

◆ AddClassesXMLTo()

void TMVA::MethodBase::AddClassesXMLTo ( void parent) const
private

write class info to XML

Definition at line 1787 of file MethodBase.cxx.

◆ AddClassifierOutput()

void TMVA::MethodBase::AddClassifierOutput ( Types::ETreeType  type)
privatevirtual

prepare tree branch with the method's discriminating variable

Definition at line 868 of file MethodBase.cxx.

◆ AddClassifierOutputProb()

void TMVA::MethodBase::AddClassifierOutputProb ( Types::ETreeType  type)
privatevirtual

prepare tree branch with the method's discriminating variable

Definition at line 936 of file MethodBase.cxx.

◆ AddInfoItem()

void TMVA::MethodBase::AddInfoItem ( void gi,
const TString name,
const TString value 
) const
private

xml writing

Definition at line 1292 of file MethodBase.cxx.

◆ AddMulticlassOutput()

void TMVA::MethodBase::AddMulticlassOutput ( Types::ETreeType  type)
privatevirtual

prepare tree branch with the method's discriminating variable

Definition at line 794 of file MethodBase.cxx.

◆ AddOutput()

void TMVA::MethodBase::AddOutput ( Types::ETreeType  type,
Types::EAnalysisType  analysisType 
)

Definition at line 1301 of file MethodBase.cxx.

◆ AddRegressionOutput()

void TMVA::MethodBase::AddRegressionOutput ( Types::ETreeType  type)
privatevirtual

prepare tree branch with the method's discriminating variable

Definition at line 744 of file MethodBase.cxx.

◆ AddSpectatorsXMLTo()

void TMVA::MethodBase::AddSpectatorsXMLTo ( void parent) const
private

write spectator info to XML

Definition at line 1764 of file MethodBase.cxx.

◆ AddTargetsXMLTo()

void TMVA::MethodBase::AddTargetsXMLTo ( void parent) const
private

write target info to XML

Definition at line 1807 of file MethodBase.cxx.

◆ AddVarsXMLTo()

void TMVA::MethodBase::AddVarsXMLTo ( void parent) const
private

write variable info to XML

Definition at line 1748 of file MethodBase.cxx.

◆ AddWeightsXMLTo()

◆ BaseDir()

TDirectory * TMVA::MethodBase::BaseDir ( ) const

returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored

Definition at line 1966 of file MethodBase.cxx.

◆ CheckSetup()

void TMVA::MethodBase::CheckSetup ( )
virtual

check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase)

Reimplemented in TMVA::MethodCuts, TMVA::MethodBoost, and TMVA::MethodFDA.

Definition at line 433 of file MethodBase.cxx.

◆ CreateMVAPdfs()

void TMVA::MethodBase::CreateMVAPdfs ( )
private

Create PDFs of the MVA output variables.

Definition at line 2171 of file MethodBase.cxx.

◆ CreateRanking()

◆ Data()

DataSet* TMVA::MethodBase::Data ( ) const
inline

Definition at line 408 of file MethodBase.h.

◆ DataInfo()

DataSetInfo& TMVA::MethodBase::DataInfo ( ) const
inline

Definition at line 409 of file MethodBase.h.

◆ DeclareBaseOptions()

void TMVA::MethodBase::DeclareBaseOptions ( )
private

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

Definition at line 509 of file MethodBase.cxx.

◆ DeclareCompatibilityOptions()

void TMVA::MethodBase::DeclareCompatibilityOptions ( )
virtual

options that are used ONLY for the READER to ensure backward compatibility they are hence without any effect (the reader is only reading the training options that HAD been used at the training of the .xml weight file at hand

Reimplemented in TMVA::MethodBDT, TMVA::MethodPDEFoam, TMVA::MethodSVM, TMVA::MethodBoost, TMVA::MethodLikelihood, TMVA::MethodKNN, TMVA::MethodCrossValidation, and TMVA::MethodDT.

Definition at line 596 of file MethodBase.cxx.

◆ DeclareOptions()

◆ DisableWriting()

void TMVA::MethodBase::DisableWriting ( Bool_t  setter)
inline

Definition at line 442 of file MethodBase.h.

◆ DoMulticlass()

Bool_t TMVA::MethodBase::DoMulticlass ( ) const
inline

Definition at line 439 of file MethodBase.h.

◆ DoRegression()

Bool_t TMVA::MethodBase::DoRegression ( ) const
inline

Definition at line 438 of file MethodBase.h.

◆ ExitFromTraining()

void TMVA::MethodBase::ExitFromTraining ( )
inline

Definition at line 462 of file MethodBase.h.

◆ GetAnalysisType()

Types::EAnalysisType TMVA::MethodBase::GetAnalysisType ( void  ) const
inline

Definition at line 437 of file MethodBase.h.

◆ GetCurrentIter()

UInt_t TMVA::MethodBase::GetCurrentIter ( )
inline

Definition at line 479 of file MethodBase.h.

◆ GetCutOrientation()

ECutOrientation TMVA::MethodBase::GetCutOrientation ( ) const
inlineprivate

Definition at line 550 of file MethodBase.h.

◆ GetEfficiency()

Double_t TMVA::MethodBase::GetEfficiency ( const TString theString,
Types::ETreeType  type,
Double_t effSerr 
)
virtual

fill background efficiency (resp.

rejection) versus signal efficiency plots returns signal efficiency at background efficiency indicated in theString

Reimplemented in TMVA::MethodCuts.

Definition at line 2288 of file MethodBase.cxx.

◆ GetEvent() [1/4]

const TMVA::Event * TMVA::MethodBase::GetEvent ( ) const
inline

Definition at line 749 of file MethodBase.h.

◆ GetEvent() [2/4]

const TMVA::Event * TMVA::MethodBase::GetEvent ( const TMVA::Event ev) const
inline

Definition at line 744 of file MethodBase.h.

◆ GetEvent() [3/4]

const TMVA::Event * TMVA::MethodBase::GetEvent ( Long64_t  ievt) const
inline

Definition at line 757 of file MethodBase.h.

◆ GetEvent() [4/4]

const TMVA::Event * TMVA::MethodBase::GetEvent ( Long64_t  ievt,
Types::ETreeType  type 
) const
inline

Definition at line 763 of file MethodBase.h.

◆ GetEventCollection()

const std::vector< TMVA::Event * > & TMVA::MethodBase::GetEventCollection ( Types::ETreeType  type)

returns the event collection (i.e.

the dataset) TRANSFORMED using the classifiers specific Variable Transformation (e.g. Decorr or Decorr:Gauss:Decorr)

Definition at line 3337 of file MethodBase.cxx.

◆ GetFile()

TFile* TMVA::MethodBase::GetFile ( ) const
inline

Definition at line 369 of file MethodBase.h.

◆ GetInputLabel()

const TString& TMVA::MethodBase::GetInputLabel ( Int_t  i) const
inline

Definition at line 349 of file MethodBase.h.

◆ GetInputTitle()

const char* TMVA::MethodBase::GetInputTitle ( Int_t  i) const
inline

Definition at line 350 of file MethodBase.h.

◆ GetInputVar()

const TString& TMVA::MethodBase::GetInputVar ( Int_t  i) const
inline

Definition at line 348 of file MethodBase.h.

◆ GetInteractiveTrainingError()

TMultiGraph* TMVA::MethodBase::GetInteractiveTrainingError ( )
inline

Definition at line 459 of file MethodBase.h.

◆ GetInternalVarName()

const TString& TMVA::MethodBase::GetInternalVarName ( Int_t  ivar) const
inlineprotected

Definition at line 508 of file MethodBase.h.

◆ GetJobName()

const TString& TMVA::MethodBase::GetJobName ( ) const
inline

Definition at line 329 of file MethodBase.h.

◆ GetKSTrainingVsTest()

Double_t TMVA::MethodBase::GetKSTrainingVsTest ( Char_t  SorB,
TString  opt = "X" 
)
virtual

Definition at line 3382 of file MethodBase.cxx.

◆ GetLine()

Bool_t TMVA::MethodBase::GetLine ( std::istream &  fin,
char *  buf 
)
private

reads one line from the input stream checks for certain keywords and interprets the line if keywords are found

Definition at line 2128 of file MethodBase.cxx.

◆ GetMaximumSignificance()

Double_t TMVA::MethodBase::GetMaximumSignificance ( Double_t  SignalEvents,
Double_t  BackgroundEvents,
Double_t optimal_significance_value 
) const
virtual

plot significance, \( \frac{S}{\sqrt{S^2 + B^2}} \), curve for given number of signal and background events; returns cut for maximum significance also returned via reference is the maximum significance

Definition at line 2872 of file MethodBase.cxx.

◆ GetMaxIter()

UInt_t TMVA::MethodBase::GetMaxIter ( )
inline

Definition at line 476 of file MethodBase.h.

◆ GetMean()

Double_t TMVA::MethodBase::GetMean ( Int_t  ivar) const
inline

Definition at line 353 of file MethodBase.h.

◆ GetMethodName()

const TString& TMVA::MethodBase::GetMethodName ( ) const
inline

Definition at line 330 of file MethodBase.h.

◆ GetMethodType()

Types::EMVA TMVA::MethodBase::GetMethodType ( ) const
inline

Definition at line 332 of file MethodBase.h.

◆ GetMethodTypeName()

TString TMVA::MethodBase::GetMethodTypeName ( ) const
inline

Definition at line 331 of file MethodBase.h.

◆ GetMulticlassConfusionMatrix()

TMatrixD TMVA::MethodBase::GetMulticlassConfusionMatrix ( Double_t  effB,
Types::ETreeType  type 
)
virtual

Construct a confusion matrix for a multiclass classifier.

The confusion matrix compares, in turn, each class agaist all other classes in a pair-wise fashion. In rows with index \( k_r = 0 ... K \), \( k_r \) is considered signal for the sake of comparison and for each column \( k_c = 0 ... K \) the corresponding class is considered background.

Note that the diagonal elements will be returned as NaN since this will compare a class against itself.

See also
TMVA::ResultsMulticlass::GetConfusionMatrix
Parameters
[in]effBThe background efficiency for which to evaluate.
[in]typeThe data set on which to evaluate (training, testing ...).
Returns
A matrix containing signal efficiencies for the given background efficiency. The diagonal elements are NaN since this measure is meaningless (comparing a class against itself).

Definition at line 2736 of file MethodBase.cxx.

◆ GetMulticlassEfficiency()

std::vector< Float_t > TMVA::MethodBase::GetMulticlassEfficiency ( std::vector< std::vector< Float_t > > &  purity)
virtual

Definition at line 2689 of file MethodBase.cxx.

◆ GetMulticlassTrainingEfficiency()

std::vector< Float_t > TMVA::MethodBase::GetMulticlassTrainingEfficiency ( std::vector< std::vector< Float_t > > &  purity)
virtual

Definition at line 2701 of file MethodBase.cxx.

◆ GetMulticlassValues()

virtual const std::vector<Float_t>& TMVA::MethodBase::GetMulticlassValues ( )
inlinevirtual

◆ GetMvaValue() [1/2]

◆ GetMvaValue() [2/2]

Double_t TMVA::MethodBase::GetMvaValue ( const TMVA::Event *const  ev,
Double_t err = 0,
Double_t errUpper = 0 
)

Definition at line 843 of file MethodBase.cxx.

◆ GetMvaValues()

std::vector< Double_t > TMVA::MethodBase::GetMvaValues ( Long64_t  firstEvt = 0,
Long64_t  lastEvt = -1,
Bool_t  logProgress = false 
)
protectedvirtual

get all the MVA values for the events of the current Data type

Reimplemented in TMVA::MethodDL, TMVA::PyMethodBase, TMVA::MethodRSNNS, TMVA::MethodRXGB, TMVA::MethodRSVM, TMVA::MethodC50, TMVA::MethodPyAdaBoost, TMVA::MethodPyRandomForest, TMVA::MethodPyKeras, and TMVA::MethodPyGTB.

Definition at line 894 of file MethodBase.cxx.

◆ GetName()

const char* TMVA::MethodBase::GetName ( ) const
inlinevirtual

Implements TMVA::IMethod.

Definition at line 333 of file MethodBase.h.

◆ GetNEvents()

UInt_t TMVA::MethodBase::GetNEvents ( void  ) const
inline

temporary event when testing on a different DataSet than the own one

Definition at line 416 of file MethodBase.h.

◆ GetNTargets()

UInt_t TMVA::MethodBase::GetNTargets ( ) const
inline

Definition at line 345 of file MethodBase.h.

◆ GetNvar()

UInt_t TMVA::MethodBase::GetNvar ( ) const
inline

Definition at line 343 of file MethodBase.h.

◆ GetNVariables()

UInt_t TMVA::MethodBase::GetNVariables ( ) const
inline

Definition at line 344 of file MethodBase.h.

◆ GetOriginalVarName()

const TString& TMVA::MethodBase::GetOriginalVarName ( Int_t  ivar) const
inlineprotected

Definition at line 509 of file MethodBase.h.

◆ GetProba() [1/2]

Double_t TMVA::MethodBase::GetProba ( const Event ev)
virtual

Definition at line 2233 of file MethodBase.cxx.

◆ GetProba() [2/2]

Double_t TMVA::MethodBase::GetProba ( Double_t  mvaVal,
Double_t  ap_sig 
)
virtual

compute likelihood ratio

Definition at line 2250 of file MethodBase.cxx.

◆ GetProbaName()

const TString TMVA::MethodBase::GetProbaName ( ) const
inline

Definition at line 335 of file MethodBase.h.

◆ GetRarity()

Double_t TMVA::MethodBase::GetRarity ( Double_t  mvaVal,
Types::ESBType  reftype = Types::kBackground 
) const
virtual

compute rarity:

\[ R(x) = \int_{[-\infty..x]} { PDF(x') dx' } \]

where PDF(x) is the PDF of the classifier's signal or background distribution

Reimplemented in TMVA::MethodCuts.

Definition at line 2271 of file MethodBase.cxx.

◆ GetRegressionDeviation()

void TMVA::MethodBase::GetRegressionDeviation ( UInt_t  tgtNum,
Types::ETreeType  type,
Double_t stddev,
Double_t stddev90Percent 
) const
virtual

Definition at line 724 of file MethodBase.cxx.

◆ GetRegressionValues() [1/2]

const std::vector<Float_t>& TMVA::MethodBase::GetRegressionValues ( const TMVA::Event *const  ev)
inline

Definition at line 213 of file MethodBase.h.

◆ GetRegressionValues() [2/2]

◆ GetRMS()

Double_t TMVA::MethodBase::GetRMS ( Int_t  ivar) const
inline

Definition at line 354 of file MethodBase.h.

◆ GetROCIntegral() [1/2]

Double_t TMVA::MethodBase::GetROCIntegral ( TH1D histS,
TH1D histB 
) const
virtual

calculate the area (integral) under the ROC curve as a overall quality measure of the classification

Definition at line 2808 of file MethodBase.cxx.

◆ GetROCIntegral() [2/2]

Double_t TMVA::MethodBase::GetROCIntegral ( PDF pdfS = 0,
PDF pdfB = 0 
) const
virtual

calculate the area (integral) under the ROC curve as a overall quality measure of the classification

Definition at line 2842 of file MethodBase.cxx.

◆ GetSeparation() [1/2]

Double_t TMVA::MethodBase::GetSeparation ( TH1 histoS,
TH1 histoB 
) const
virtual

compute "separation" defined as

\[ <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } \]

Reimplemented in TMVA::MethodCuts.

Definition at line 2775 of file MethodBase.cxx.

◆ GetSeparation() [2/2]

Double_t TMVA::MethodBase::GetSeparation ( PDF pdfS = 0,
PDF pdfB = 0 
) const
virtual

compute "separation" defined as

\[ <s2> = \frac{1}{2} \int_{-\infty}^{+\infty} { \frac{(S(x) - B(x))^2}{(S(x) + B(x))} dx } \]

Reimplemented in TMVA::MethodCuts.

Definition at line 2786 of file MethodBase.cxx.

◆ GetSignalReferenceCut()

Double_t TMVA::MethodBase::GetSignalReferenceCut ( ) const
inline

Definition at line 359 of file MethodBase.h.

◆ GetSignalReferenceCutOrientation()

Double_t TMVA::MethodBase::GetSignalReferenceCutOrientation ( ) const
inline

Definition at line 360 of file MethodBase.h.

◆ GetSignificance()

Double_t TMVA::MethodBase::GetSignificance ( void  ) const
virtual

compute significance of mean difference

\[ significance = \frac{|<S> - <B>|}{\sqrt{RMS_{S2} + RMS_{B2}}} \]

Reimplemented in TMVA::MethodCuts.

Definition at line 2762 of file MethodBase.cxx.

◆ GetTestingEvent()

const TMVA::Event * TMVA::MethodBase::GetTestingEvent ( Long64_t  ievt) const
inline

Definition at line 775 of file MethodBase.h.

◆ GetTestTime()

Double_t TMVA::MethodBase::GetTestTime ( ) const
inline

Definition at line 166 of file MethodBase.h.

◆ GetTestvarName()

const TString& TMVA::MethodBase::GetTestvarName ( ) const
inline

Definition at line 334 of file MethodBase.h.

◆ GetTrainingEfficiency()

Double_t TMVA::MethodBase::GetTrainingEfficiency ( const TString theString)
virtual

Reimplemented in TMVA::MethodCuts.

Definition at line 2514 of file MethodBase.cxx.

◆ GetTrainingEvent()

const TMVA::Event * TMVA::MethodBase::GetTrainingEvent ( Long64_t  ievt) const
inline

Definition at line 769 of file MethodBase.h.

◆ GetTrainingHistory()

virtual const std::vector<Float_t>& TMVA::MethodBase::GetTrainingHistory ( const char *  )
inlinevirtual

Definition at line 232 of file MethodBase.h.

◆ GetTrainingROOTVersionCode()

UInt_t TMVA::MethodBase::GetTrainingROOTVersionCode ( ) const
inline

Definition at line 389 of file MethodBase.h.

◆ GetTrainingROOTVersionString()

TString TMVA::MethodBase::GetTrainingROOTVersionString ( ) const

calculates the ROOT version string from the training version code on the fly

Definition at line 3371 of file MethodBase.cxx.

◆ GetTrainingTMVAVersionCode()

UInt_t TMVA::MethodBase::GetTrainingTMVAVersionCode ( ) const
inline

Definition at line 388 of file MethodBase.h.

◆ GetTrainingTMVAVersionString()

TString TMVA::MethodBase::GetTrainingTMVAVersionString ( ) const

calculates the TMVA version string from the training version code on the fly

Definition at line 3359 of file MethodBase.cxx.

◆ GetTrainTime()

Double_t TMVA::MethodBase::GetTrainTime ( ) const
inline

Definition at line 162 of file MethodBase.h.

◆ GetTransformationHandler() [1/2]

TransformationHandler& TMVA::MethodBase::GetTransformationHandler ( Bool_t  takeReroutedIfAvailable = true)
inline

Definition at line 393 of file MethodBase.h.

◆ GetTransformationHandler() [2/2]

const TransformationHandler& TMVA::MethodBase::GetTransformationHandler ( Bool_t  takeReroutedIfAvailable = true) const
inline

Definition at line 397 of file MethodBase.h.

◆ GetValueForRoot()

Double_t TMVA::MethodBase::GetValueForRoot ( Double_t  theCut)
privatevirtual

returns efficiency as function of cut

Definition at line 3310 of file MethodBase.cxx.

◆ GetWeightFileDir()

const TString& TMVA::MethodBase::GetWeightFileDir ( ) const
inlineprotected

Definition at line 490 of file MethodBase.h.

◆ GetWeightFileName()

TString TMVA::MethodBase::GetWeightFileName ( ) const

retrieve weight file name

Definition at line 2062 of file MethodBase.cxx.

◆ GetXmax()

Double_t TMVA::MethodBase::GetXmax ( Int_t  ivar) const
inline

Definition at line 356 of file MethodBase.h.

◆ GetXmin()

Double_t TMVA::MethodBase::GetXmin ( Int_t  ivar) const
inline

Definition at line 355 of file MethodBase.h.

◆ HasMVAPdfs()

Bool_t TMVA::MethodBase::HasMVAPdfs ( ) const
inline

Definition at line 435 of file MethodBase.h.

◆ HasTrainingTree()

Bool_t TMVA::MethodBase::HasTrainingTree ( ) const
inlineprotected

Definition at line 511 of file MethodBase.h.

◆ Help()

Bool_t TMVA::MethodBase::Help ( ) const
inlineprotected

Definition at line 502 of file MethodBase.h.

◆ IgnoreEventsWithNegWeightsInTraining()

Bool_t TMVA::MethodBase::IgnoreEventsWithNegWeightsInTraining ( ) const
inlineprotected

Definition at line 684 of file MethodBase.h.

◆ Init()

◆ InitBase()

void TMVA::MethodBase::InitBase ( )
private

default initialization called by all constructors

Definition at line 441 of file MethodBase.cxx.

◆ InitIPythonInteractive()

void TMVA::MethodBase::InitIPythonInteractive ( )
inline

Definition at line 453 of file MethodBase.h.

◆ IsConstructedFromWeightFile()

Bool_t TMVA::MethodBase::IsConstructedFromWeightFile ( ) const
inlineprotected

Definition at line 538 of file MethodBase.h.

◆ IsModelPersistence()

Bool_t TMVA::MethodBase::IsModelPersistence ( ) const
inline

Definition at line 382 of file MethodBase.h.

◆ IsNormalised()

Bool_t TMVA::MethodBase::IsNormalised ( ) const
inlineprotected

Definition at line 494 of file MethodBase.h.

◆ IsSignalLike() [1/2]

Bool_t TMVA::MethodBase::IsSignalLike ( )
virtual

uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event would be selected as signal or background

Definition at line 854 of file MethodBase.cxx.

◆ IsSignalLike() [2/2]

Bool_t TMVA::MethodBase::IsSignalLike ( Double_t  mvaVal)
virtual

uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event with this mva output value would be selected as signal or background

Definition at line 861 of file MethodBase.cxx.

◆ IsSilentFile()

Bool_t TMVA::MethodBase::IsSilentFile ( ) const
inline

Definition at line 378 of file MethodBase.h.

◆ MakeClass()

void TMVA::MethodBase::MakeClass ( const TString classFileName = TString("")) const
virtual

create reader class for method (classification only at present)

Implements TMVA::IMethod.

Reimplemented in TMVA::MethodCategory, TMVA::MethodTMlpANN, TMVA::MethodC50, and TMVA::MethodRXGB.

Definition at line 2993 of file MethodBase.cxx.

◆ MakeClassSpecific()

◆ MakeClassSpecificHeader()

virtual void TMVA::MethodBase::MakeClassSpecificHeader ( std::ostream &  ,
const TString = "" 
) const
inlineprotectedvirtual

◆ MethodBaseDir()

TDirectory * TMVA::MethodBase::MethodBaseDir ( ) const

returns the ROOT directory where all instances of the corresponding MVA method are stored

Definition at line 2006 of file MethodBase.cxx.

◆ NoErrorCalc()

void TMVA::MethodBase::NoErrorCalc ( Double_t *const  err,
Double_t *const  errUpper 
)
protected

Definition at line 836 of file MethodBase.cxx.

◆ OptimizeTuningParameters()

std::map< TString, Double_t > TMVA::MethodBase::OptimizeTuningParameters ( TString  fomType = "ROCIntegral",
TString  fitType = "FitGA" 
)
virtual

call the Optimizer with the set of parameters and ranges that are meant to be tuned.

Reimplemented in TMVA::MethodBDT, and TMVA::MethodSVM.

Definition at line 623 of file MethodBase.cxx.

◆ PrintHelpMessage()

void TMVA::MethodBase::PrintHelpMessage ( ) const
virtual

prints out method-specific help method

Implements TMVA::IMethod.

Definition at line 3254 of file MethodBase.cxx.

◆ ProcessBaseOptions()

void TMVA::MethodBase::ProcessBaseOptions ( )
private

the option string is decoded, for available options see "DeclareOptions"

Definition at line 540 of file MethodBase.cxx.

◆ ProcessOptions()

◆ ProcessSetup()

void TMVA::MethodBase::ProcessSetup ( )

process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase)

Definition at line 423 of file MethodBase.cxx.

◆ ReadClassesFromXML()

void TMVA::MethodBase::ReadClassesFromXML ( void clsnode)
private

read number of classes from XML

Definition at line 1903 of file MethodBase.cxx.

◆ ReadSpectatorsFromXML()

void TMVA::MethodBase::ReadSpectatorsFromXML ( void specnode)
private

read spectator info from XML

Definition at line 1863 of file MethodBase.cxx.

◆ ReadStateFromFile()

void TMVA::MethodBase::ReadStateFromFile ( )

Function to write options and weights to file.

Definition at line 1412 of file MethodBase.cxx.

◆ ReadStateFromStream() [1/2]

void TMVA::MethodBase::ReadStateFromStream ( std::istream &  tf)

read the header from the weight files of the different MVA methods

Definition at line 1576 of file MethodBase.cxx.

◆ ReadStateFromStream() [2/2]

void TMVA::MethodBase::ReadStateFromStream ( TFile rf)

write reference MVA distributions (and other information) to a ROOT type weight file

Definition at line 1371 of file MethodBase.cxx.

◆ ReadStateFromXML()

void TMVA::MethodBase::ReadStateFromXML ( void parent)
private

Definition at line 1466 of file MethodBase.cxx.

◆ ReadStateFromXMLString()

void TMVA::MethodBase::ReadStateFromXMLString ( const char *  xmlstr)

for reading from memory

Definition at line 1455 of file MethodBase.cxx.

◆ ReadTargetsFromXML()

void TMVA::MethodBase::ReadTargetsFromXML ( void tarnode)
private

read target info from XML

Definition at line 1945 of file MethodBase.cxx.

◆ ReadVariablesFromXML()

void TMVA::MethodBase::ReadVariablesFromXML ( void varnode)
private

read variable info from XML

Definition at line 1823 of file MethodBase.cxx.

◆ ReadVarsFromStream()

void TMVA::MethodBase::ReadVarsFromStream ( std::istream &  istr)
private

Read the variables (name, min, max) for a given data transformation method from the stream.

In the stream we only expect the limits which will be set

Definition at line 1711 of file MethodBase.cxx.

◆ ReadWeightsFromStream() [1/2]

◆ ReadWeightsFromStream() [2/2]

virtual void TMVA::MethodBase::ReadWeightsFromStream ( TFile )
inlineprotectedvirtual

◆ ReadWeightsFromXML()

◆ RerouteTransformationHandler()

void TMVA::MethodBase::RerouteTransformationHandler ( TransformationHandler fTargetTransformation)
inline

Definition at line 402 of file MethodBase.h.

◆ Reset()

virtual void TMVA::MethodBase::Reset ( void  )
inlinevirtual

◆ ResetThisBase()

void TMVA::MethodBase::ResetThisBase ( )
private

◆ SetAnalysisType()

virtual void TMVA::MethodBase::SetAnalysisType ( Types::EAnalysisType  type)
inlinevirtual

Definition at line 436 of file MethodBase.h.

◆ SetBaseDir()

void TMVA::MethodBase::SetBaseDir ( TDirectory methodDir)
inline

Definition at line 372 of file MethodBase.h.

◆ SetFile()

void TMVA::MethodBase::SetFile ( TFile file)
inline

Definition at line 374 of file MethodBase.h.

◆ SetMethodBaseDir()

void TMVA::MethodBase::SetMethodBaseDir ( TDirectory methodDir)
inline

Definition at line 373 of file MethodBase.h.

◆ SetMethodDir()

void TMVA::MethodBase::SetMethodDir ( TDirectory methodDir)
inline

Definition at line 371 of file MethodBase.h.

◆ SetModelPersistence()

void TMVA::MethodBase::SetModelPersistence ( Bool_t  status)
inline

Definition at line 381 of file MethodBase.h.

◆ SetNormalised()

void TMVA::MethodBase::SetNormalised ( Bool_t  norm)
inlineprotected

Definition at line 495 of file MethodBase.h.

◆ SetSignalReferenceCut()

void TMVA::MethodBase::SetSignalReferenceCut ( Double_t  cut)
inline

Definition at line 363 of file MethodBase.h.

◆ SetSignalReferenceCutOrientation()

void TMVA::MethodBase::SetSignalReferenceCutOrientation ( Double_t  cutOrientation)
inline

Definition at line 364 of file MethodBase.h.

◆ SetSilentFile()

void TMVA::MethodBase::SetSilentFile ( Bool_t  status)
inline

Definition at line 377 of file MethodBase.h.

◆ SetTestTime()

void TMVA::MethodBase::SetTestTime ( Double_t  testTime)
inline

Definition at line 165 of file MethodBase.h.

◆ SetTestvarName()

void TMVA::MethodBase::SetTestvarName ( const TString v = "")
inline

Definition at line 340 of file MethodBase.h.

◆ SetTrainTime()

void TMVA::MethodBase::SetTrainTime ( Double_t  trainTime)
inline

Definition at line 161 of file MethodBase.h.

◆ SetTuneParameters()

void TMVA::MethodBase::SetTuneParameters ( std::map< TString, Double_t tuneParameters)
virtual

set the tuning parameters according to the argument This is just a dummy .

. have a look at the MethodBDT how you could perhaps implement the same thing for the other Classifiers..

Reimplemented in TMVA::MethodBDT, and TMVA::MethodSVM.

Definition at line 644 of file MethodBase.cxx.

◆ SetupMethod()

void TMVA::MethodBase::SetupMethod ( )

setup of methods

Definition at line 406 of file MethodBase.cxx.

◆ SetWeightFileDir()

void TMVA::MethodBase::SetWeightFileDir ( TString  fileDir)
protected

set directory of weight file

Definition at line 2045 of file MethodBase.cxx.

◆ SetWeightFileName()

void TMVA::MethodBase::SetWeightFileName ( TString  theWeightFile)
protected

set the weight file name (depreciated)

Definition at line 2054 of file MethodBase.cxx.

◆ Statistics()

void TMVA::MethodBase::Statistics ( Types::ETreeType  treeType,
const TString theVarName,
Double_t meanS,
Double_t meanB,
Double_t rmsS,
Double_t rmsB,
Double_t xmin,
Double_t xmax 
)
protected

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

Definition at line 2928 of file MethodBase.cxx.

◆ TestClassification()

void TMVA::MethodBase::TestClassification ( )
virtual

◆ TestMulticlass()

void TMVA::MethodBase::TestMulticlass ( )
virtual

test multiclass classification

Definition at line 1084 of file MethodBase.cxx.

◆ TestRegression()

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,
Types::ETreeType  type 
)
virtual

calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample

  • bias = average deviation
  • dev = average absolute deviation
  • rms = rms of deviation

Definition at line 977 of file MethodBase.cxx.

◆ Train()

◆ TrainingEnded()

bool TMVA::MethodBase::TrainingEnded ( )
inline

Definition at line 467 of file MethodBase.h.

◆ TrainMethod()

void TMVA::MethodBase::TrainMethod ( )

Definition at line 650 of file MethodBase.cxx.

◆ TxtWeightsOnly()

Bool_t TMVA::MethodBase::TxtWeightsOnly ( ) const
inlineprotected

Definition at line 532 of file MethodBase.h.

◆ Verbose()

Bool_t TMVA::MethodBase::Verbose ( void  ) const
inlineprotected

Definition at line 501 of file MethodBase.h.

◆ WriteEvaluationHistosToFile()

void TMVA::MethodBase::WriteEvaluationHistosToFile ( Types::ETreeType  treetype)
virtual

writes all MVA evaluation histograms to file

Reimplemented in TMVA::MethodBoost.

Definition at line 2080 of file MethodBase.cxx.

◆ WriteMonitoringHistosToFile()

void TMVA::MethodBase::WriteMonitoringHistosToFile ( void  ) const
virtual

write special monitoring histograms to file dummy implementation here --------------—

Implements TMVA::IMethod.

Reimplemented in TMVA::MethodBoost, TMVA::MethodANNBase, TMVA::MethodBDT, TMVA::MethodCuts, TMVA::MethodLikelihood, TMVA::MethodRuleFit, and TMVA::MethodCrossValidation.

Definition at line 2119 of file MethodBase.cxx.

◆ WriteStateToFile()

void TMVA::MethodBase::WriteStateToFile ( ) const

write options and weights to file note that each one text file for the main configuration information and one ROOT file for ROOT objects are created

Definition at line 1390 of file MethodBase.cxx.

◆ WriteStateToStream()

void TMVA::MethodBase::WriteStateToStream ( std::ostream &  tf) const
private

general method used in writing the header of the weight files where the used variables, variable transformation type etc.

is specified

Definition at line 1253 of file MethodBase.cxx.

◆ WriteStateToXML()

void TMVA::MethodBase::WriteStateToXML ( void parent) const
private

general method used in writing the header of the weight files where the used variables, variable transformation type etc.

is specified

Definition at line 1317 of file MethodBase.cxx.

◆ WriteVarsToStream()

void TMVA::MethodBase::WriteVarsToStream ( std::ostream &  tf,
const TString prefix = "" 
) const
private

write the list of variables (name, min, max) for a given data transformation method to the stream

Definition at line 1696 of file MethodBase.cxx.

Friends And Related Function Documentation

◆ CrossValidation

friend class CrossValidation
friend

Definition at line 113 of file MethodBase.h.

◆ Experimental::Classification

friend class Experimental::Classification
friend

Definition at line 118 of file MethodBase.h.

◆ Factory

friend class Factory
friend

Definition at line 114 of file MethodBase.h.

◆ MethodBoost

friend class MethodBoost
friend

Definition at line 116 of file MethodBase.h.

◆ MethodCategory

friend class MethodCategory
friend

Definition at line 268 of file MethodBase.h.

◆ MethodCompositeBase

friend class MethodCompositeBase
friend

Definition at line 269 of file MethodBase.h.

◆ MethodCrossValidation

friend class MethodCrossValidation
friend

Definition at line 117 of file MethodBase.h.

◆ MethodCuts

friend class MethodCuts
friend

Definition at line 601 of file MethodBase.h.

◆ RootFinder

friend class RootFinder
friend

Definition at line 115 of file MethodBase.h.

Member Data Documentation

◆ fAnalysisType

Types::EAnalysisType TMVA::MethodBase::fAnalysisType
protected

Definition at line 593 of file MethodBase.h.

◆ fBackgroundClass

UInt_t TMVA::MethodBase::fBackgroundClass
protected

Definition at line 688 of file MethodBase.h.

◆ fBaseDir

TDirectory* TMVA::MethodBase::fBaseDir
private

Definition at line 623 of file MethodBase.h.

◆ fConstructedFromWeightFile

Bool_t TMVA::MethodBase::fConstructedFromWeightFile
private

Definition at line 618 of file MethodBase.h.

◆ fCutOrientation

ECutOrientation TMVA::MethodBase::fCutOrientation
private

Definition at line 697 of file MethodBase.h.

◆ fDataSetInfo

DataSetInfo& TMVA::MethodBase::fDataSetInfo
private

Definition at line 605 of file MethodBase.h.

◆ fDefaultPDF

PDF* TMVA::MethodBase::fDefaultPDF
private

Definition at line 642 of file MethodBase.h.

◆ fEffS

TH1* TMVA::MethodBase::fEffS
private

Definition at line 640 of file MethodBase.h.

◆ fEventCollections

std::vector<const std::vector<TMVA::Event*>*> TMVA::MethodBase::fEventCollections
mutableprivate

Definition at line 706 of file MethodBase.h.

◆ fExitFromTraining

bool TMVA::MethodBase::fExitFromTraining = false
protected

Definition at line 447 of file MethodBase.h.

◆ fFile

TFile* TMVA::MethodBase::fFile
private

Definition at line 626 of file MethodBase.h.

◆ fFileDir

TString TMVA::MethodBase::fFileDir
private

Definition at line 635 of file MethodBase.h.

◆ fHasMVAPdfs

Bool_t TMVA::MethodBase::fHasMVAPdfs
private

Definition at line 678 of file MethodBase.h.

◆ fHelp

Bool_t TMVA::MethodBase::fHelp
private

Definition at line 677 of file MethodBase.h.

◆ fIgnoreNegWeightsInTraining

Bool_t TMVA::MethodBase::fIgnoreNegWeightsInTraining
private

Definition at line 680 of file MethodBase.h.

◆ fInputVars

std::vector<TString>* TMVA::MethodBase::fInputVars
protected

Definition at line 586 of file MethodBase.h.

◆ fInteractive

IPythonInteractive* TMVA::MethodBase::fInteractive = nullptr
protected

Definition at line 446 of file MethodBase.h.

◆ fIPyCurrentIter

UInt_t TMVA::MethodBase::fIPyCurrentIter = 0
protected

Definition at line 448 of file MethodBase.h.

◆ fIPyMaxIter

UInt_t TMVA::MethodBase::fIPyMaxIter = 0
protected

Definition at line 448 of file MethodBase.h.

◆ fJobName

TString TMVA::MethodBase::fJobName
private

Definition at line 612 of file MethodBase.h.

◆ fMeanB

Double_t TMVA::MethodBase::fMeanB
private

Definition at line 660 of file MethodBase.h.

◆ fMeanS

Double_t TMVA::MethodBase::fMeanS
private

Definition at line 659 of file MethodBase.h.

◆ fMethodBaseDir

TDirectory* TMVA::MethodBase::fMethodBaseDir
mutableprivate

Definition at line 624 of file MethodBase.h.

◆ fMethodName

TString TMVA::MethodBase::fMethodName
private

Definition at line 613 of file MethodBase.h.

◆ fMethodType

Types::EMVA TMVA::MethodBase::fMethodType
private

Definition at line 614 of file MethodBase.h.

◆ fModelPersistence

Bool_t TMVA::MethodBase::fModelPersistence
private

Definition at line 631 of file MethodBase.h.

◆ fMulticlassReturnVal

std::vector<Float_t>* TMVA::MethodBase::fMulticlassReturnVal
protected

Definition at line 596 of file MethodBase.h.

◆ fMVAPdfB

PDF* TMVA::MethodBase::fMVAPdfB
private

Definition at line 644 of file MethodBase.h.

◆ fMVAPdfS

PDF* TMVA::MethodBase::fMVAPdfS
private

Definition at line 643 of file MethodBase.h.

◆ fNbins

Int_t TMVA::MethodBase::fNbins
protected

Definition at line 589 of file MethodBase.h.

◆ fNbinsH

Int_t TMVA::MethodBase::fNbinsH
protected

Definition at line 591 of file MethodBase.h.

◆ fNbinsMVAoutput

Int_t TMVA::MethodBase::fNbinsMVAoutput
protected

Definition at line 590 of file MethodBase.h.

◆ fNbinsMVAPdf

Int_t TMVA::MethodBase::fNbinsMVAPdf
private

Definition at line 724 of file MethodBase.h.

◆ fNormalise

Bool_t TMVA::MethodBase::fNormalise
private

Definition at line 720 of file MethodBase.h.

◆ fNsmoothMVAPdf

Int_t TMVA::MethodBase::fNsmoothMVAPdf
private

Definition at line 725 of file MethodBase.h.

◆ fParentDir

TString TMVA::MethodBase::fParentDir
private

Definition at line 633 of file MethodBase.h.

◆ fRanking

Ranking* TMVA::MethodBase::fRanking
protected

Definition at line 585 of file MethodBase.h.

◆ fRegressionReturnVal

std::vector<Float_t>* TMVA::MethodBase::fRegressionReturnVal
protected

Definition at line 595 of file MethodBase.h.

◆ fResults

Results* TMVA::MethodBase::fResults
protected

Definition at line 728 of file MethodBase.h.

◆ fRmsB

Double_t TMVA::MethodBase::fRmsB
private

Definition at line 662 of file MethodBase.h.

◆ fRmsS

Double_t TMVA::MethodBase::fRmsS
private

Definition at line 661 of file MethodBase.h.

◆ fROOTTrainingVersion

UInt_t TMVA::MethodBase::fROOTTrainingVersion
private

Definition at line 617 of file MethodBase.h.

◆ fSetupCompleted

Bool_t TMVA::MethodBase::fSetupCompleted

Definition at line 709 of file MethodBase.h.

◆ fSignalClass

UInt_t TMVA::MethodBase::fSignalClass
protected

Definition at line 687 of file MethodBase.h.

◆ fSignalReferenceCut

Double_t TMVA::MethodBase::fSignalReferenceCut
private

the data set information (sometimes needed)

Definition at line 607 of file MethodBase.h.

◆ fSignalReferenceCutOrientation

Double_t TMVA::MethodBase::fSignalReferenceCutOrientation
private

Definition at line 608 of file MethodBase.h.

◆ fSilentFile

Bool_t TMVA::MethodBase::fSilentFile
private

Definition at line 629 of file MethodBase.h.

◆ fSplB

PDF* TMVA::MethodBase::fSplB
private

Definition at line 649 of file MethodBase.h.

◆ fSpleffBvsS

TSpline* TMVA::MethodBase::fSpleffBvsS
private

Definition at line 650 of file MethodBase.h.

◆ fSplRefB

TSpline1* TMVA::MethodBase::fSplRefB
private

Definition at line 701 of file MethodBase.h.

◆ fSplRefS

TSpline1* TMVA::MethodBase::fSplRefS
private

Definition at line 700 of file MethodBase.h.

◆ fSplS

PDF* TMVA::MethodBase::fSplS
private

Definition at line 648 of file MethodBase.h.

◆ fSplTrainB

PDF* TMVA::MethodBase::fSplTrainB
private

Definition at line 653 of file MethodBase.h.

◆ fSplTrainEffBvsS

TSpline* TMVA::MethodBase::fSplTrainEffBvsS
private

Definition at line 654 of file MethodBase.h.

◆ fSplTrainRefB

TSpline1* TMVA::MethodBase::fSplTrainRefB
private

Definition at line 704 of file MethodBase.h.

◆ fSplTrainRefS

TSpline1* TMVA::MethodBase::fSplTrainRefS
private

Definition at line 703 of file MethodBase.h.

◆ fSplTrainS

PDF* TMVA::MethodBase::fSplTrainS
private

Definition at line 652 of file MethodBase.h.

◆ fTestTime

Double_t TMVA::MethodBase::fTestTime
private

Definition at line 694 of file MethodBase.h.

◆ fTestvar

TString TMVA::MethodBase::fTestvar
private

Definition at line 615 of file MethodBase.h.

◆ fTmpEvent

const Event* TMVA::MethodBase::fTmpEvent
mutable

Definition at line 411 of file MethodBase.h.

◆ fTMVATrainingVersion

UInt_t TMVA::MethodBase::fTMVATrainingVersion
private

Definition at line 616 of file MethodBase.h.

◆ fTrainHistory

TrainingHistory TMVA::MethodBase::fTrainHistory

Definition at line 425 of file MethodBase.h.

◆ fTrainTime

Double_t TMVA::MethodBase::fTrainTime
private

Definition at line 693 of file MethodBase.h.

◆ fTransformation

TransformationHandler TMVA::MethodBase::fTransformation
private

Definition at line 670 of file MethodBase.h.

◆ fTransformationPointer

TransformationHandler* TMVA::MethodBase::fTransformationPointer
private

Definition at line 669 of file MethodBase.h.

◆ fTxtWeightsOnly

Bool_t TMVA::MethodBase::fTxtWeightsOnly
private

Definition at line 723 of file MethodBase.h.

◆ fUseDecorr

Bool_t TMVA::MethodBase::fUseDecorr
private

Definition at line 721 of file MethodBase.h.

◆ fVariableTransformType

Types::ESBType TMVA::MethodBase::fVariableTransformType
private

Definition at line 609 of file MethodBase.h.

◆ fVariableTransformTypeString

TString TMVA::MethodBase::fVariableTransformTypeString
private

Definition at line 722 of file MethodBase.h.

◆ fVarTransformString

TString TMVA::MethodBase::fVarTransformString
private

Definition at line 667 of file MethodBase.h.

◆ fVerbose

Bool_t TMVA::MethodBase::fVerbose
private

Definition at line 674 of file MethodBase.h.

◆ fVerbosityLevel

EMsgType TMVA::MethodBase::fVerbosityLevel
private

Definition at line 676 of file MethodBase.h.

◆ fVerbosityLevelString

TString TMVA::MethodBase::fVerbosityLevelString
private

Definition at line 675 of file MethodBase.h.

◆ fWeightFile

TString TMVA::MethodBase::fWeightFile
private

Definition at line 636 of file MethodBase.h.

◆ fXmax

Double_t TMVA::MethodBase::fXmax
private

Definition at line 664 of file MethodBase.h.

◆ fXmin

Double_t TMVA::MethodBase::fXmin
private

Definition at line 663 of file MethodBase.h.

Libraries for TMVA::MethodBase:
[legend]

The documentation for this class was generated from the following files: