ROOT   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 ,
}

enum  { kSingleKey = (1ULL << ( 0 )) , kOverwrite = (1ULL << ( 1 )) , kWriteDelete = (1ULL << ( 2 )) }

enum  EDeprecatedStatusBits { kObjInCanvas = (1ULL << ( 3 )) }

enum  EStatusBits {
kCanDelete = (1ULL << ( 0 )) , kMustCleanup = (1ULL << ( 3 )) , kIsReferenced = (1ULL << ( 4 )) , kHasUUID = (1ULL << ( 5 )) ,
kCannotPick = (1ULL << ( 6 )) , kNoContextMenu = (1ULL << ( 8 )) , kInvalidObject = (1ULL << ( 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 ()

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

virtual Double_t GetMvaValue (Double_t *errLower=nullptr, Double_t *errUpper=nullptr)=0

const char * GetName () const

UInt_t GetNEvents () const

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: More...

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

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

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

Double_t GetRMS (Int_t ivar) const

virtual Double_t GetROCIntegral (PDF *pdfS=nullptr, PDF *pdfB=nullptr) const
calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...

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

virtual Double_t GetSeparation (TH1 *, TH1 *) const
compute "separation" defined as More...

Double_t GetSignalReferenceCut () const

Double_t GetSignalReferenceCutOrientation () const

virtual Double_t GetSignificance () const
compute significance of mean difference 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 ()

virtual TClassIsA () const

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...

Function to write options and weights to file. More...

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

write reference MVA distributions (and other information) to a ROOT type weight file 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 Streamer (TBuffer &)
Stream an object of class TObject. More...

void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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 const RankingCreateRanking ()=0

virtual void DeclareOptions ()=0

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

virtual const char * GetName () const =0

virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)=0

virtual void Init ()=0

virtual TClassIsA () const

virtual void MakeClass (const TString &classFileName=TString("")) const =0

virtual void PrintHelpMessage () const =0

virtual void ProcessOptions ()=0

virtual void Streamer (TBuffer &)

void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

virtual void Train (void)=0

virtual void WriteMonitoringHistosToFile (void) const =0

Public Member Functions inherited from TMVA::Configurable
Configurable (const TString &theOption="")
constructor More...

virtual ~Configurable ()
default destructor More...

write options to XML file More...

template<class 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 >
TMVA::OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc)

template<class T >
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)

template<class T >
OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")

const char * GetConfigDescription () const

const char * GetConfigName () const

const TStringGetOptions () const

virtual TClassIsA () 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...

read option back from the weight file More...

void SetConfigDescription (const char *d)

void SetConfigName (const char *n)

void SetMsgType (EMsgType t)

void SetOptions (const TString &s)

virtual void Streamer (TBuffer &)
Stream an object of class TObject. More...

void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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 TNamed &named)
TNamed copy ctor. More...

TNamed (const TString &name, const TString &title)

virtual ~TNamed ()
TNamed destructor. More...

void Clear (Option_t *option="") override
Set name and title to empty strings (""). More...

TObjectClone (const char *newname="") const override
Make a clone of an object using the Streamer facility. More...

Int_t Compare (const TObject *obj) const override
Compare two TNamed objects. More...

void Copy (TObject &named) const override
Copy this to obj. More...

virtual void FillBuffer (char *&buffer)
Encode TNamed into output buffer. More...

const char * GetName () const override
Returns name of object. More...

const char * GetTitle () const override
Returns title of object. More...

ULong_t Hash () const override
Return hash value for this object. More...

TClassIsA () const override

Bool_t IsSortable () const override

void ls (Option_t *option="") const override
List TNamed name and title. More...

TNamedoperator= (const TNamed &rhs)
TNamed assignment operator. More...

void Print (Option_t *option="") const override
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...

void Streamer (TBuffer &) override
Stream an object of class TObject. More...

void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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...

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 Clear (Option_t *="")

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 abstract method. More...

virtual void Copy (TObject &object) const
Copy this to obj. 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 with: gROOT->SetSelectedPad(c1). 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=nullptr)
Execute method on this object with the given parameter string, e.g. More...

virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=nullptr)
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 const char * GetName () const
Returns 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 const char * GetTitle () const
Returns title of object. More...

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...

virtual ULong_t Hash () const
Return hash value for this object. 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 TClassIsA () const

Bool_t IsDestructed () const
IsDestructed. More...

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

virtual Bool_t IsSortable () const

R__ALWAYS_INLINE Bool_t IsZombie () const

virtual void ls (Option_t *option="") const
The ls function lists the contents of a class on stdout. More...

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...

void * operator new (size_t sz)

void * operator new (size_t sz, void *vp)

void * operator new[] (size_t sz)

void * operator 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 void Print (Option_t *option="") const
This method must be overridden when a class wants to print itself. 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)

void SetBit (UInt_t f, Bool_t set)
Set or unset the user status bits as specified in f. More...

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 Streamer (TBuffer &)
Stream an object of class TObject. More...

void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

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=nullptr, Int_t option=0, Int_t bufsize=0)
Write this object to the current directory. More...

virtual Int_t Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) const
Write this object to the current directory. More...

## Static Public Member Functions

static TClassClass ()

static const char * Class_Name ()

static constexpr Version_t Class_Version ()

static const char * DeclFileName ()

Static Public Member Functions inherited from TMVA::IMethod
static TClassClass ()

static const char * Class_Name ()

static constexpr Version_t Class_Version ()

static const char * DeclFileName ()

Static Public Member Functions inherited from TMVA::Configurable
static TClassClass ()

static const char * Class_Name ()

static constexpr Version_t Class_Version ()

static const char * DeclFileName ()

Static Public Member Functions inherited from TNamed
static TClassClass ()

static const char * Class_Name ()

static constexpr Version_t Class_Version ()

static const char * DeclFileName ()

Static Public Member Functions inherited from TObject
static TClassClass ()

static const char * Class_Name ()

static constexpr Version_t Class_Version ()

static const char * DeclFileName ()

static Longptr_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...

## Public Attributes

Bool_t fSetupCompleted

TrainingHistory fTrainHistory

## Protected Member Functions

virtual void AddWeightsXMLTo (void *parent) const =0

virtual std::vector< Double_tGetDataMvaValues (DataSet *data=nullptr, Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false)
get all the MVA values for the events of the given Data type More...

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)

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

virtual void MakeClassSpecific (std::ostream &, const TString &) 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
temporary dataset used when evaluating on a different data (used by MethodCategory::GetMvaValues) More...

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

DataSetfTmpData = nullptr
temporary event when testing on a different DataSet than the own one More...

const EventfTmpEvent

Protected Attributes inherited from TMVA::Configurable
MsgLoggerfLogger
! message logger More...

Protected Attributes inherited from TNamed
TString fName

TString fTitle

## Private Types

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

## Private Member Functions

write class info to XML More...

prepare tree branch with the method's discriminating variable More...

prepare tree branch with the method's discriminating variable More...

void AddInfoItem (void *gi, const TString &name, const TString &value) const
xml writing More...

prepare tree branch with the method's discriminating variable More...

prepare tree branch with the method's discriminating variable More...

write spectator info to XML More...

write target info to XML More...

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...

read number of classes from XML More...

read spectator info from XML More...

read target info from XML More...

read variable info from XML More...

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
default PDF definitions More...

TH1fEffS
efficiency histogram for rootfinder More...

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

TFilefFile

TString fFileDir
unix sub-directory for weight files (default: DataLoader's Name + "weights") More...

Bool_t fHasMVAPdfs
MVA Pdfs are created for this classifier. More...

Bool_t fHelp
help flag More...

Bool_t fIgnoreNegWeightsInTraining
If true, events with negative weights are not used in training. More...

TString fJobName

Double_t fMeanB
mean (background) More...

Double_t fMeanS
mean (signal) More...

TDirectoryfMethodBaseDir

TString fMethodName

Types::EMVA fMethodType

Bool_t fModelPersistence

PDFfMVAPdfB
background MVA PDF More...

PDFfMVAPdfS
signal MVA PDF More...

Int_t fNbinsMVAPdf

Bool_t fNormalise

Int_t fNsmoothMVAPdf

TString fParentDir
method parent name, like booster name More...

Double_t fRmsB
RMS (background) More...

Double_t fRmsS
RMS (signal) More...

UInt_t fROOTTrainingVersion

Double_t fSignalReferenceCut
the data set information (sometimes needed) More...

Double_t fSignalReferenceCutOrientation

Bool_t fSilentFile

PDFfSplB
PDFs of MVA distribution (background) More...

TSplinefSpleffBvsS
splines for signal eff. versus background eff. More...

TSpline1fSplRefB

TSpline1fSplRefS

PDFfSplS
PDFs of MVA distribution (signal) More...

PDFfSplTrainB
PDFs of training MVA distribution (background) More...

TSplinefSplTrainEffBvsS
splines for training signal eff. versus background eff. More...

TSpline1fSplTrainRefB

TSpline1fSplTrainRefS

PDFfSplTrainS
PDFs of training MVA distribution (signal) More...

Double_t fTestTime

TString fTestvar

UInt_t fTMVATrainingVersion

Double_t fTrainTime

TransformationHandler fTransformation
the list of transformations More...

TransformationHandlerfTransformationPointer
pointer to the rest of transformations More...

Bool_t fTxtWeightsOnly

Bool_t fUseDecorr

Types::ESBType fVariableTransformType

TString fVariableTransformTypeString

TString fVarTransformString
labels variable transform method More...

Bool_t fVerbose
verbose flag More...

EMsgType fVerbosityLevel
verbosity level More...

TString fVerbosityLevelString
verbosity level (user input string) More...

TString fWeightFile
weight file name More...

Double_t fXmax
maximum (signal and background) More...

Double_t fXmin
minimum (signal and background) More...

## Friends

class CrossValidation

class Experimental::Classification

class Factory

class MethodBoost

class MethodCategory

class MethodCompositeBase

class MethodCrossValidation

class MethodCuts

class RootFinder

Protected Types inherited from TObject
enum  { kOnlyPrepStep = (1ULL << ( 3 )) }

#include <TMVA/MethodBase.h>

Inheritance diagram for TMVA::MethodBase:
[legend]

## ◆ ECutOrientation

 private
Enumerator
kNegative
kPositive

Definition at line 551 of file MethodBase.h.

## ◆ EWeightFileType

Enumerator
kROOT
kTEXT

Definition at line 122 of file MethodBase.h.

## ◆ 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

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

write class info to XML

Definition at line 1802 of file MethodBase.cxx.

 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.

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

prepare tree branch with the method's discriminating variable

Definition at line 950 of file MethodBase.cxx.

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

xml writing

Definition at line 1307 of file MethodBase.cxx.

 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.

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

Definition at line 1316 of file MethodBase.cxx.

 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.

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

write spectator info to XML

Definition at line 1779 of file MethodBase.cxx.

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

write target info to XML

Definition at line 1822 of file MethodBase.cxx.

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

write variable info to XML

Definition at line 1763 of file MethodBase.cxx.

 virtual void TMVA::MethodBase::AddWeightsXMLTo ( void * parent ) const
protectedpure virtual

## ◆ 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 1981 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::MethodBoost, TMVA::MethodCuts, and TMVA::MethodFDA.

Definition at line 433 of file MethodBase.cxx.

## ◆ Class()

 static TClass * TMVA::MethodBase::Class ( )
static
Returns
TClass describing this class

## ◆ Class_Name()

 static const char * TMVA::MethodBase::Class_Name ( )
static
Returns
Name of this class

## ◆ Class_Version()

 static constexpr Version_t TMVA::MethodBase::Class_Version ( )
inlinestaticconstexpr
Returns
Version of this class

Definition at line 731 of file MethodBase.h.

## ◆ CreateMVAPdfs()

 void TMVA::MethodBase::CreateMVAPdfs ( )
private

Create PDFs of the MVA output variables.

Definition at line 2186 of file MethodBase.cxx.

## ◆ CreateRanking()

 virtual const Ranking * TMVA::MethodBase::CreateRanking ( )
pure virtual

## ◆ Data()

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

Definition at line 409 of file MethodBase.h.

## ◆ DataInfo()

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

Definition at line 410 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

Definition at line 596 of file MethodBase.cxx.

## ◆ DeclareOptions()

 virtual void TMVA::MethodBase::DeclareOptions ( )
pure virtual

## ◆ DeclFileName()

 static const char * TMVA::MethodBase::DeclFileName ( )
inlinestatic
Returns
Name of the file containing the class declaration

Definition at line 731 of file MethodBase.h.

## ◆ 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 464 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 481 of file MethodBase.h.

## ◆ GetCutOrientation()

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

Definition at line 552 of file MethodBase.h.

## ◆ GetDataMvaValues()

 std::vector< Double_t > TMVA::MethodBase::GetDataMvaValues ( DataSet * data = nullptr, Long64_t firstEvt = 0, Long64_t lastEvt = -1, Bool_t logProgress = false )
protectedvirtual

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

Definition at line 939 of file MethodBase.cxx.

## ◆ 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 2303 of file MethodBase.cxx.

## ◆ GetEvent() [1/4]

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

Definition at line 751 of file MethodBase.h.

## ◆ GetEvent() [2/4]

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

Definition at line 746 of file MethodBase.h.

## ◆ GetEvent() [3/4]

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

Definition at line 759 of file MethodBase.h.

## ◆ GetEvent() [4/4]

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

Definition at line 765 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 3348 of file MethodBase.cxx.

## ◆ GetFile()

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

Definition at line 370 of file MethodBase.h.

## ◆ GetInputLabel()

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

Definition at line 350 of file MethodBase.h.

## ◆ GetInputTitle()

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

Definition at line 351 of file MethodBase.h.

## ◆ GetInputVar()

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

Definition at line 349 of file MethodBase.h.

## ◆ GetInteractiveTrainingError()

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

Definition at line 461 of file MethodBase.h.

## ◆ GetInternalVarName()

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

Definition at line 510 of file MethodBase.h.

## ◆ GetJobName()

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

Definition at line 330 of file MethodBase.h.

## ◆ GetKSTrainingVsTest()

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

Definition at line 3393 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 2143 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 2887 of file MethodBase.cxx.

## ◆ GetMaxIter()

 UInt_t TMVA::MethodBase::GetMaxIter ( )
inline

Definition at line 478 of file MethodBase.h.

## ◆ GetMean()

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

Definition at line 354 of file MethodBase.h.

## ◆ GetMethodName()

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

Definition at line 331 of file MethodBase.h.

## ◆ GetMethodType()

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

Definition at line 333 of file MethodBase.h.

## ◆ GetMethodTypeName()

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

Definition at line 332 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.

TMVA::ResultsMulticlass::GetConfusionMatrix
Parameters
 [in] effB The background efficiency for which to evaluate. [in] type The 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 2751 of file MethodBase.cxx.

## ◆ GetMulticlassEfficiency()

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

Definition at line 2704 of file MethodBase.cxx.

## ◆ GetMulticlassTrainingEfficiency()

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

Definition at line 2716 of file MethodBase.cxx.

## ◆ GetMulticlassValues()

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

Definition at line 227 of file MethodBase.h.

## ◆ GetMvaValue() [1/2]

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

Definition at line 843 of file MethodBase.cxx.

## ◆ GetMvaValue() [2/2]

 virtual Double_t TMVA::MethodBase::GetMvaValue ( Double_t * errLower = nullptr, Double_t * errUpper = nullptr )
pure virtual

## ◆ 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

Definition at line 897 of file MethodBase.cxx.

## ◆ GetName()

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

Implements TMVA::IMethod.

Definition at line 334 of file MethodBase.h.

## ◆ GetNEvents()

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

Definition at line 416 of file MethodBase.h.

## ◆ GetNTargets()

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

Definition at line 346 of file MethodBase.h.

## ◆ GetNvar()

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

Definition at line 344 of file MethodBase.h.

## ◆ GetNVariables()

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

Definition at line 345 of file MethodBase.h.

## ◆ GetOriginalVarName()

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

Definition at line 511 of file MethodBase.h.

## ◆ GetProba() [1/2]

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

Definition at line 2248 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 2265 of file MethodBase.cxx.

## ◆ GetProbaName()

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

Definition at line 336 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 2286 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]

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

Definition at line 221 of file MethodBase.h.

## ◆ GetRegressionValues() [2/2]

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

Definition at line 214 of file MethodBase.h.

## ◆ GetRMS()

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

Definition at line 355 of file MethodBase.h.

## ◆ GetROCIntegral() [1/2]

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

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

Definition at line 2857 of file MethodBase.cxx.

## ◆ GetROCIntegral() [2/2]

 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 2823 of file MethodBase.cxx.

## ◆ GetSeparation() [1/2]

 Double_t TMVA::MethodBase::GetSeparation ( PDF * pdfS = nullptr, PDF * pdfB = nullptr ) 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 2801 of file MethodBase.cxx.

## ◆ GetSeparation() [2/2]

 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 2790 of file MethodBase.cxx.

## ◆ GetSignalReferenceCut()

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

Definition at line 360 of file MethodBase.h.

## ◆ GetSignalReferenceCutOrientation()

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

Definition at line 361 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 2777 of file MethodBase.cxx.

## ◆ GetTestingEvent()

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

Definition at line 777 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 335 of file MethodBase.h.

## ◆ GetTrainingEfficiency()

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

Reimplemented in TMVA::MethodCuts.

Definition at line 2529 of file MethodBase.cxx.

## ◆ GetTrainingEvent()

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

Definition at line 771 of file MethodBase.h.

## ◆ GetTrainingHistory()

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

Definition at line 233 of file MethodBase.h.

## ◆ GetTrainingROOTVersionCode()

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

Definition at line 390 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 3382 of file MethodBase.cxx.

## ◆ GetTrainingTMVAVersionCode()

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

Definition at line 389 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 3370 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 394 of file MethodBase.h.

## ◆ GetTransformationHandler() [2/2]

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

Definition at line 398 of file MethodBase.h.

## ◆ GetValueForRoot()

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

returns efficiency as function of cut

Definition at line 3321 of file MethodBase.cxx.

## ◆ GetWeightFileDir()

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

Definition at line 492 of file MethodBase.h.

## ◆ GetWeightFileName()

 TString TMVA::MethodBase::GetWeightFileName ( ) const

retrieve weight file name

Definition at line 2077 of file MethodBase.cxx.

## ◆ GetXmax()

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

Definition at line 357 of file MethodBase.h.

## ◆ GetXmin()

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

Definition at line 356 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 513 of file MethodBase.h.

## ◆ Help()

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

Definition at line 504 of file MethodBase.h.

## ◆ IgnoreEventsWithNegWeightsInTraining()

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

Definition at line 686 of file MethodBase.h.

## ◆ Init()

 virtual void TMVA::MethodBase::Init ( )
pure virtual

## ◆ 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 455 of file MethodBase.h.

## ◆ IsA()

 virtual TClass * TMVA::MethodBase::IsA ( ) const
inlinevirtual
Returns
TClass describing current object

Reimplemented from TMVA::Configurable.

Definition at line 731 of file MethodBase.h.

## ◆ IsConstructedFromWeightFile()

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

Definition at line 540 of file MethodBase.h.

## ◆ IsModelPersistence()

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

Definition at line 383 of file MethodBase.h.

## ◆ IsNormalised()

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

Definition at line 496 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 379 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::MethodC50, TMVA::MethodRXGB, and TMVA::MethodTMlpANN.

Definition at line 3004 of file MethodBase.cxx.

## ◆ MakeClassSpecific()

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

Implements TMVA::IMethod.

Definition at line 520 of file MethodBase.h.

 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 2021 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 3265 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()

 virtual void TMVA::MethodBase::ProcessOptions ( )
pure virtual

## ◆ 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.

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

read number of classes from XML

Definition at line 1918 of file MethodBase.cxx.

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

Definition at line 1878 of file MethodBase.cxx.

Function to write options and weights to file.

Definition at line 1427 of file MethodBase.cxx.

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

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

Definition at line 1591 of file MethodBase.cxx.

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

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

Definition at line 1386 of file MethodBase.cxx.

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

Definition at line 1481 of file MethodBase.cxx.

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

Definition at line 1470 of file MethodBase.cxx.

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

Definition at line 1960 of file MethodBase.cxx.

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

Definition at line 1838 of file MethodBase.cxx.

 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 1726 of file MethodBase.cxx.

 virtual void TMVA::MethodBase::ReadWeightsFromStream ( std::istream & )
protectedpure virtual

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

 virtual void TMVA::MethodBase::ReadWeightsFromXML ( void * wghtnode )
protectedpure virtual

## ◆ RerouteTransformationHandler()

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

Definition at line 403 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 373 of file MethodBase.h.

## ◆ SetFile()

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

Definition at line 375 of file MethodBase.h.

## ◆ SetMethodBaseDir()

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

Definition at line 374 of file MethodBase.h.

## ◆ SetMethodDir()

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

Definition at line 372 of file MethodBase.h.

## ◆ SetModelPersistence()

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

Definition at line 382 of file MethodBase.h.

## ◆ SetNormalised()

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

Definition at line 497 of file MethodBase.h.

## ◆ SetSignalReferenceCut()

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

Definition at line 364 of file MethodBase.h.

## ◆ SetSignalReferenceCutOrientation()

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

Definition at line 365 of file MethodBase.h.

## ◆ SetSilentFile()

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

Definition at line 378 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 341 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 2060 of file MethodBase.cxx.

## ◆ SetWeightFileName()

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

set the weight file name (depreciated)

Definition at line 2069 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 2943 of file MethodBase.cxx.

## ◆ Streamer()

 virtual void TMVA::MethodBase::Streamer ( TBuffer & R__b )
virtual

## ◆ StreamerNVirtual()

 void TMVA::MethodBase::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )
inline

Definition at line 731 of file MethodBase.h.

## ◆ TestClassification()

 void TMVA::MethodBase::TestClassification ( )
virtual

initialization

Definition at line 1126 of file MethodBase.cxx.

## ◆ TestMulticlass()

 void TMVA::MethodBase::TestMulticlass ( )
virtual

test multiclass classification

Definition at line 1099 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 991 of file MethodBase.cxx.

## ◆ Train()

 virtual void TMVA::MethodBase::Train ( )
pure virtual

## ◆ TrainingEnded()

 bool TMVA::MethodBase::TrainingEnded ( )
inline

Definition at line 469 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 534 of file MethodBase.h.

## ◆ Verbose()

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

Definition at line 503 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 2095 of file MethodBase.cxx.

## ◆ WriteMonitoringHistosToFile()

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

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

Implements TMVA::IMethod.

Definition at line 2134 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 1405 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 1268 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 1332 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 1711 of file MethodBase.cxx.

## ◆ 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 269 of file MethodBase.h.

## ◆ MethodCompositeBase

 friend class MethodCompositeBase
friend

Definition at line 270 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 603 of file MethodBase.h.

## ◆ RootFinder

 friend class RootFinder
friend

Definition at line 115 of file MethodBase.h.

## ◆ fAnalysisType

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

Definition at line 595 of file MethodBase.h.

## ◆ fBackgroundClass

 UInt_t TMVA::MethodBase::fBackgroundClass
protected

Definition at line 690 of file MethodBase.h.

## ◆ fBaseDir

 TDirectory* TMVA::MethodBase::fBaseDir
private

Definition at line 625 of file MethodBase.h.

## ◆ fConstructedFromWeightFile

 Bool_t TMVA::MethodBase::fConstructedFromWeightFile
private

Definition at line 620 of file MethodBase.h.

## ◆ fCutOrientation

 ECutOrientation TMVA::MethodBase::fCutOrientation
private

Definition at line 699 of file MethodBase.h.

## ◆ fDataSetInfo

 DataSetInfo& TMVA::MethodBase::fDataSetInfo
private

Definition at line 607 of file MethodBase.h.

## ◆ fDefaultPDF

 PDF* TMVA::MethodBase::fDefaultPDF
private

default PDF definitions

Definition at line 644 of file MethodBase.h.

## ◆ fEffS

 TH1* TMVA::MethodBase::fEffS
private

efficiency histogram for rootfinder

Definition at line 642 of file MethodBase.h.

## ◆ fEventCollections

 std::vector*> TMVA::MethodBase::fEventCollections
mutableprivate

Definition at line 708 of file MethodBase.h.

## ◆ fExitFromTraining

 bool TMVA::MethodBase::fExitFromTraining = false
protected

Definition at line 449 of file MethodBase.h.

## ◆ fFile

 TFile* TMVA::MethodBase::fFile
private

Definition at line 628 of file MethodBase.h.

## ◆ fFileDir

 TString TMVA::MethodBase::fFileDir
private

unix sub-directory for weight files (default: DataLoader's Name + "weights")

Definition at line 637 of file MethodBase.h.

## ◆ fHasMVAPdfs

 Bool_t TMVA::MethodBase::fHasMVAPdfs
private

MVA Pdfs are created for this classifier.

Definition at line 680 of file MethodBase.h.

## ◆ fHelp

 Bool_t TMVA::MethodBase::fHelp
private

help flag

Definition at line 679 of file MethodBase.h.

## ◆ fIgnoreNegWeightsInTraining

 Bool_t TMVA::MethodBase::fIgnoreNegWeightsInTraining
private

If true, events with negative weights are not used in training.

Definition at line 682 of file MethodBase.h.

## ◆ fInputVars

 std::vector* TMVA::MethodBase::fInputVars
protected

Definition at line 588 of file MethodBase.h.

## ◆ fInteractive

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

temporary dataset used when evaluating on a different data (used by MethodCategory::GetMvaValues)

Definition at line 448 of file MethodBase.h.

## ◆ fIPyCurrentIter

 UInt_t TMVA::MethodBase::fIPyCurrentIter = 0
protected

Definition at line 450 of file MethodBase.h.

## ◆ fIPyMaxIter

 UInt_t TMVA::MethodBase::fIPyMaxIter = 0
protected

Definition at line 450 of file MethodBase.h.

## ◆ fJobName

 TString TMVA::MethodBase::fJobName
private

Definition at line 614 of file MethodBase.h.

## ◆ fMeanB

 Double_t TMVA::MethodBase::fMeanB
private

mean (background)

Definition at line 662 of file MethodBase.h.

## ◆ fMeanS

 Double_t TMVA::MethodBase::fMeanS
private

mean (signal)

Definition at line 661 of file MethodBase.h.

## ◆ fMethodBaseDir

 TDirectory* TMVA::MethodBase::fMethodBaseDir
mutableprivate

Definition at line 626 of file MethodBase.h.

## ◆ fMethodName

 TString TMVA::MethodBase::fMethodName
private

Definition at line 615 of file MethodBase.h.

## ◆ fMethodType

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

Definition at line 616 of file MethodBase.h.

## ◆ fModelPersistence

 Bool_t TMVA::MethodBase::fModelPersistence
private

Definition at line 633 of file MethodBase.h.

## ◆ fMulticlassReturnVal

 std::vector* TMVA::MethodBase::fMulticlassReturnVal
protected

Definition at line 598 of file MethodBase.h.

## ◆ fMVAPdfB

 PDF* TMVA::MethodBase::fMVAPdfB
private

background MVA PDF

Definition at line 646 of file MethodBase.h.

## ◆ fMVAPdfS

 PDF* TMVA::MethodBase::fMVAPdfS
private

signal MVA PDF

Definition at line 645 of file MethodBase.h.

## ◆ fNbins

 Int_t TMVA::MethodBase::fNbins
protected

Definition at line 591 of file MethodBase.h.

## ◆ fNbinsH

 Int_t TMVA::MethodBase::fNbinsH
protected

Definition at line 593 of file MethodBase.h.

## ◆ fNbinsMVAoutput

 Int_t TMVA::MethodBase::fNbinsMVAoutput
protected

Definition at line 592 of file MethodBase.h.

## ◆ fNbinsMVAPdf

 Int_t TMVA::MethodBase::fNbinsMVAPdf
private

Definition at line 726 of file MethodBase.h.

## ◆ fNormalise

 Bool_t TMVA::MethodBase::fNormalise
private

Definition at line 722 of file MethodBase.h.

## ◆ fNsmoothMVAPdf

 Int_t TMVA::MethodBase::fNsmoothMVAPdf
private

Definition at line 727 of file MethodBase.h.

## ◆ fParentDir

 TString TMVA::MethodBase::fParentDir
private

method parent name, like booster name

Definition at line 635 of file MethodBase.h.

## ◆ fRanking

 Ranking* TMVA::MethodBase::fRanking
protected

Definition at line 587 of file MethodBase.h.

## ◆ fRegressionReturnVal

 std::vector* TMVA::MethodBase::fRegressionReturnVal
protected

Definition at line 597 of file MethodBase.h.

## ◆ fResults

 Results* TMVA::MethodBase::fResults
protected

Definition at line 730 of file MethodBase.h.

## ◆ fRmsB

 Double_t TMVA::MethodBase::fRmsB
private

RMS (background)

Definition at line 664 of file MethodBase.h.

## ◆ fRmsS

 Double_t TMVA::MethodBase::fRmsS
private

RMS (signal)

Definition at line 663 of file MethodBase.h.

## ◆ fROOTTrainingVersion

 UInt_t TMVA::MethodBase::fROOTTrainingVersion
private

Definition at line 619 of file MethodBase.h.

## ◆ fSetupCompleted

 Bool_t TMVA::MethodBase::fSetupCompleted

Definition at line 711 of file MethodBase.h.

## ◆ fSignalClass

 UInt_t TMVA::MethodBase::fSignalClass
protected

Definition at line 689 of file MethodBase.h.

## ◆ fSignalReferenceCut

 Double_t TMVA::MethodBase::fSignalReferenceCut
private

the data set information (sometimes needed)

Definition at line 609 of file MethodBase.h.

## ◆ fSignalReferenceCutOrientation

 Double_t TMVA::MethodBase::fSignalReferenceCutOrientation
private

Definition at line 610 of file MethodBase.h.

## ◆ fSilentFile

 Bool_t TMVA::MethodBase::fSilentFile
private

Definition at line 631 of file MethodBase.h.

## ◆ fSplB

 PDF* TMVA::MethodBase::fSplB
private

PDFs of MVA distribution (background)

Definition at line 651 of file MethodBase.h.

## ◆ fSpleffBvsS

 TSpline* TMVA::MethodBase::fSpleffBvsS
private

splines for signal eff. versus background eff.

Definition at line 652 of file MethodBase.h.

## ◆ fSplRefB

 TSpline1* TMVA::MethodBase::fSplRefB
private

Definition at line 703 of file MethodBase.h.

## ◆ fSplRefS

 TSpline1* TMVA::MethodBase::fSplRefS
private

Definition at line 702 of file MethodBase.h.

## ◆ fSplS

 PDF* TMVA::MethodBase::fSplS
private

PDFs of MVA distribution (signal)

Definition at line 650 of file MethodBase.h.

## ◆ fSplTrainB

 PDF* TMVA::MethodBase::fSplTrainB
private

PDFs of training MVA distribution (background)

Definition at line 655 of file MethodBase.h.

## ◆ fSplTrainEffBvsS

 TSpline* TMVA::MethodBase::fSplTrainEffBvsS
private

splines for training signal eff. versus background eff.

Definition at line 656 of file MethodBase.h.

## ◆ fSplTrainRefB

 TSpline1* TMVA::MethodBase::fSplTrainRefB
private

Definition at line 706 of file MethodBase.h.

## ◆ fSplTrainRefS

 TSpline1* TMVA::MethodBase::fSplTrainRefS
private

Definition at line 705 of file MethodBase.h.

## ◆ fSplTrainS

 PDF* TMVA::MethodBase::fSplTrainS
private

PDFs of training MVA distribution (signal)

Definition at line 654 of file MethodBase.h.

## ◆ fTestTime

 Double_t TMVA::MethodBase::fTestTime
private

Definition at line 696 of file MethodBase.h.

## ◆ fTestvar

 TString TMVA::MethodBase::fTestvar
private

Definition at line 617 of file MethodBase.h.

## ◆ fTmpData

 DataSet* TMVA::MethodBase::fTmpData = nullptr
protected

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

Definition at line 446 of file MethodBase.h.

## ◆ fTmpEvent

 const Event* TMVA::MethodBase::fTmpEvent
mutableprotected

Definition at line 445 of file MethodBase.h.

## ◆ fTMVATrainingVersion

 UInt_t TMVA::MethodBase::fTMVATrainingVersion
private

Definition at line 618 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 695 of file MethodBase.h.

## ◆ fTransformation

 TransformationHandler TMVA::MethodBase::fTransformation
private

the list of transformations

Definition at line 672 of file MethodBase.h.

## ◆ fTransformationPointer

 TransformationHandler* TMVA::MethodBase::fTransformationPointer
private

pointer to the rest of transformations

Definition at line 671 of file MethodBase.h.

## ◆ fTxtWeightsOnly

 Bool_t TMVA::MethodBase::fTxtWeightsOnly
private

Definition at line 725 of file MethodBase.h.

## ◆ fUseDecorr

 Bool_t TMVA::MethodBase::fUseDecorr
private

Definition at line 723 of file MethodBase.h.

## ◆ fVariableTransformType

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

Definition at line 611 of file MethodBase.h.

## ◆ fVariableTransformTypeString

 TString TMVA::MethodBase::fVariableTransformTypeString
private

Definition at line 724 of file MethodBase.h.

## ◆ fVarTransformString

 TString TMVA::MethodBase::fVarTransformString
private

labels variable transform method

Definition at line 669 of file MethodBase.h.

## ◆ fVerbose

 Bool_t TMVA::MethodBase::fVerbose
private

verbose flag

Definition at line 676 of file MethodBase.h.

## ◆ fVerbosityLevel

 EMsgType TMVA::MethodBase::fVerbosityLevel
private

verbosity level

Definition at line 678 of file MethodBase.h.

## ◆ fVerbosityLevelString

 TString TMVA::MethodBase::fVerbosityLevelString
private

verbosity level (user input string)

Definition at line 677 of file MethodBase.h.

## ◆ fWeightFile

 TString TMVA::MethodBase::fWeightFile
private

weight file name

Definition at line 638 of file MethodBase.h.

## ◆ fXmax

 Double_t TMVA::MethodBase::fXmax
private

maximum (signal and background)

Definition at line 666 of file MethodBase.h.

## ◆ fXmin

 Double_t TMVA::MethodBase::fXmin
private

minimum (signal and background)

Definition at line 665 of file MethodBase.h.

Libraries for TMVA::MethodBase:
[legend]

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