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TMVA::MethodBoost Class Reference

Class for boosting a TMVA method.

This class is meant to boost a single classifier. Boosting means training the classifier a few times. Every time the weights of the events are modified according to how well the classifier performed on the test sample.

Definition at line 58 of file MethodBoost.h.

Public Member Functions

 MethodBoost (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
 
 MethodBoost (DataSetInfo &dsi, const TString &theWeightFile)
 
virtual ~MethodBoost (void)
 destructor
 
Bool_t BookMethod (Types::EMVA theMethod, TString methodTitle, TString theOption)
 just registering the string from which the boosted classifier will be created
 
void CleanBoostOptions ()
 
const RankingCreateRanking ()
 
Int_t GetBoostNum ()
 
Double_t GetMvaValue (Double_t *err=nullptr, Double_t *errUpper=nullptr)
 return boosted MVA response
 
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t)
 Boost can handle classification with 2 classes and regression with one regression-target.
 
virtual TClassIsA () const
 
void SetBoostedMethodName (TString methodName)
 
virtual void Streamer (TBuffer &)
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
void Train (void)
 
- Public Member Functions inherited from TMVA::MethodCompositeBase
 MethodCompositeBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
 
 MethodCompositeBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile)
 
virtual ~MethodCompositeBase (void)
 delete methods
 
void AddWeightsXMLTo (void *parent) const
 
Double_t GetMvaValue (const TMVA::Event *const ev, Double_t *err=nullptr, Double_t *errUpper=nullptr)
 
Double_t GetMvaValue (Double_t *err=nullptr, Double_t *errUpper=nullptr)
 return composite MVA response
 
virtual Double_t GetMvaValue (Double_t *errLower=nullptr, Double_t *errUpper=nullptr)=0
 
virtual void ReadWeightsFromStream (std::istream &)=0
 
void ReadWeightsFromStream (std::istream &istr)
 text streamer
 
virtual void ReadWeightsFromStream (TFile &)
 
void ReadWeightsFromXML (void *wghtnode)
 XML streamer.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- Public Member Functions inherited from TMVA::MethodBase
 MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="")
 standard constructor
 
 MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile)
 constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles
 
virtual ~MethodBase ()
 destructor
 
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
 
DataSetData () const
 
DataSetInfoDataInfo () const
 
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.
 
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.
 
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
 
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.
 
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)
 
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
 
const TString GetProbaName () const
 
virtual Double_t GetRarity (Double_t mvaVal, Types::ESBType reftype=Types::kBackground) const
 compute rarity:
 
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
 
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
 
virtual Double_t GetSeparation (PDF *pdfS=nullptr, PDF *pdfB=nullptr) const
 compute "separation" defined as
 
virtual Double_t GetSeparation (TH1 *, TH1 *) const
 compute "separation" defined as
 
Double_t GetSignalReferenceCut () const
 
Double_t GetSignalReferenceCutOrientation () const
 
virtual Double_t GetSignificance () const
 compute significance of mean difference
 
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
 
UInt_t GetTrainingTMVAVersionCode () const
 
TString GetTrainingTMVAVersionString () const
 calculates the TMVA version string from the training version code on the fly
 
Double_t GetTrainTime () const
 
TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true)
 
const TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true) const
 
TString GetWeightFileName () const
 retrieve weight file name
 
Double_t GetXmax (Int_t ivar) const
 
Double_t GetXmin (Int_t ivar) const
 
Bool_t HasMVAPdfs () const
 
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
 
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
 
Bool_t IsSilentFile () const
 
virtual void MakeClass (const TString &classFileName=TString("")) const
 create reader class for method (classification only at present)
 
TDirectoryMethodBaseDir () const
 returns the ROOT directory where all instances of the corresponding MVA method are stored
 
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.
 
void PrintHelpMessage () const
 prints out method-specific help method
 
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)
 
void ReadStateFromFile ()
 Function to write options and weights to file.
 
void ReadStateFromStream (std::istream &tf)
 read the header from the weight files of the different MVA methods
 
void ReadStateFromStream (TFile &rf)
 write reference MVA distributions (and other information) to a ROOT type weight file
 
void ReadStateFromXMLString (const char *xmlstr)
 for reading from memory
 
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 .
 
void SetupMethod ()
 setup of methods
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
virtual void TestMulticlass ()
 test multiclass classification
 
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
 
bool TrainingEnded ()
 
void TrainMethod ()
 
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
 
- Public Member Functions inherited from TMVA::IMethod
 IMethod ()
 
virtual ~IMethod ()
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- Public Member Functions inherited from TMVA::Configurable
 Configurable (const TString &theOption="")
 constructor
 
virtual ~Configurable ()
 default destructor
 
void AddOptionsXMLTo (void *parent) const
 write options to XML file
 
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
 
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
 
MsgLoggerLog () const
 
virtual void ParseOptions ()
 options parser
 
void PrintOptions () const
 prints out the options set in the options string and the defaults
 
void ReadOptionsFromStream (std::istream &istr)
 read option back from the weight file
 
void ReadOptionsFromXML (void *node)
 
void SetConfigDescription (const char *d)
 
void SetConfigName (const char *n)
 
void SetMsgType (EMsgType t)
 
void SetOptions (const TString &s)
 
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
 
- Public Member Functions inherited from TNamed
 TNamed ()
 
 TNamed (const char *name, const char *title)
 
 TNamed (const TNamed &named)
 TNamed copy ctor.
 
 TNamed (const TString &name, const TString &title)
 
virtual ~TNamed ()
 TNamed destructor.
 
void Clear (Option_t *option="") override
 Set name and title to empty strings ("").
 
TObjectClone (const char *newname="") const override
 Make a clone of an object using the Streamer facility.
 
Int_t Compare (const TObject *obj) const override
 Compare two TNamed objects.
 
void Copy (TObject &named) const override
 Copy this to obj.
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer.
 
const char * GetName () const override
 Returns name of object.
 
const char * GetTitle () const override
 Returns title of object.
 
ULong_t Hash () const override
 Return hash value for this object.
 
TClassIsA () const override
 
Bool_t IsSortable () const override
 
void ls (Option_t *option="") const override
 List TNamed name and title.
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator.
 
void Print (Option_t *option="") const override
 Print TNamed name and title.
 
virtual void SetName (const char *name)
 Set the name of the TNamed.
 
virtual void SetNameTitle (const char *name, const char *title)
 Set all the TNamed parameters (name and title).
 
virtual void SetTitle (const char *title="")
 Set the title of the TNamed.
 
virtual Int_t Sizeof () const
 Return size of the TNamed part of the TObject.
 
void Streamer (TBuffer &) override
 Stream an object of class TObject.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor.
 
 TObject (const TObject &object)
 TObject copy ctor.
 
virtual ~TObject ()
 TObject destructor.
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract.
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad.
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action.
 
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.
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs.
 
virtual void Delete (Option_t *option="")
 Delete this object.
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object.
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects.
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs.
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current selected pad with: gROOT->SetSelectedPad(c1).
 
virtual void Dump () const
 Dump contents of object on stdout.
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message.
 
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.
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=nullptr)
 Execute method on this object with parameters stored in the TObjArray.
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py).
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message.
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes.
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes.
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object.
 
virtual const char * GetIconName () const
 Returns mime type name of object.
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py).
 
virtual Option_tGetOption () const
 
virtual UInt_t GetUniqueID () const
 Return the unique object id.
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out.
 
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.
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message.
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname".
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl.
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas.
 
void InvertBit (UInt_t f)
 
Bool_t IsDestructed () const
 IsDestructed.
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory).
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects).
 
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).
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification (the base implementation is no-op).
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete.
 
void operator delete (void *ptr)
 Operator delete.
 
void operator delete[] (void *ptr)
 Operator delete [].
 
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.
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself.
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list.
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory.
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list.
 
void ResetBit (UInt_t f)
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename.
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out".
 
void SetBit (UInt_t f)
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f.
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object.
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id.
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message.
 
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.
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message.
 
virtual Int_t Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory.
 
virtual Int_t Write (const char *name=nullptr, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory.
 

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::MethodCompositeBase
static TClassClass ()
 
static const char * Class_Name ()
 
static constexpr Version_t Class_Version ()
 
static const char * DeclFileName ()
 
- Static Public Member Functions inherited from TMVA::MethodBase
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.
 
static Bool_t GetObjectStat ()
 Get status of object stat flag.
 
static void SetDtorOnly (void *obj)
 Set destructor only flag.
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable.
 

Protected Member Functions

void GetHelpMessage () const
 Get help message text.
 
- Protected Member Functions inherited from TMVA::MethodCompositeBase
MethodBaseGetCurrentMethod ()
 
MethodBaseGetCurrentMethod (UInt_t idx)
 
UInt_t GetCurrentMethodIndex ()
 
IMethodGetLastMethod ()
 
IMethodGetMethod (const Int_t index) const
 accessor by index in vector
 
IMethodGetMethod (const TString &title) const
 accessor by name
 
IMethodGetPreviousMethod ()
 
- Protected Member Functions inherited from TMVA::MethodBase
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
 
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
 
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
 
void SetWeightFileName (TString)
 set the weight file name (depreciated)
 
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
 
Bool_t TxtWeightsOnly () const
 
Bool_t Verbose () const
 
- 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
 
void WriteOptionsReferenceToFile ()
 write complete options to output stream
 
- 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).
 
void MakeZombie ()
 

Private Member Functions

Double_t AdaBoost (MethodBase *method, Bool_t useYesNoLeaf)
 the standard (discrete or real) AdaBoost algorithm
 
Double_t Bagging ()
 Bagging or Bootstrap boosting, gives new random poisson weight for every event.
 
Double_t CalcMethodWeight ()
 
void CalcMVAValues ()
 
void CheckSetup ()
 check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase)
 
void ClearAll ()
 
void CreateMVAHistorgrams ()
 
MethodBaseCurrentMethod ()
 
UInt_t CurrentMethodIdx ()
 
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
 
void DeclareOptions ()
 
void FindMVACut (MethodBase *method)
 find the CUT on the individual MVA that defines an event as correct or misclassified (to be used in the boosting process)
 
Double_t GetBoostROCIntegral (Bool_t, Types::ETreeType, Bool_t CalcOverlapIntergral=kFALSE)
 Calculate the ROC integral of a single classifier or even the whole boosted classifier.
 
void Init ()
 
void InitHistos ()
 initialisation routine
 
void MonitorBoost (Types::EBoostStage stage, UInt_t methodIdx=0)
 fill various monitoring histograms from information of the individual classifiers that have been boosted.
 
void PrintResults (const TString &, std::vector< Double_t > &, const Double_t) const
 
void ProcessOptions ()
 process user options
 
void ResetBoostWeights ()
 resetting back the boosted weights of the events to 1
 
Double_t SingleBoost (MethodBase *method)
 
void SingleTrain ()
 initialization
 
virtual void TestClassification ()
 initialization
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file
 
void WriteMonitoringHistosToFile (void) const
 write special monitoring histograms to file dummy implementation here --------------—
 

Private Attributes

Double_t fAdaBoostBeta
 ADA boost parameter, default is 1.
 
Double_t fBaggedSampleFraction
 rel.Size of bagged sample
 
TString fBoostedMethodName
 details of the boosted classifier
 
TString fBoostedMethodOptions
 options
 
TString fBoostedMethodTitle
 title
 
UInt_t fBoostNum
 Number of times the classifier is boosted.
 
TString fBoostType
 string specifying the boost type
 
Double_t fBoostWeight
 the weight used to boost the next classifier
 
std::vector< TH1 * > fBTrainBgdMVAHist
 
std::vector< TH1 * > fBTrainSigMVAHist
 
DataSetManagerfDataSetManager
 DSMTEST.
 
Bool_t fDetailedMonitoring
 produce detailed monitoring histograms (boost-wise)
 
Bool_t fHistoricBoolOption
 historic variable, only needed for "CompatibilityOptions"
 
TString fHistoricOption
 historic variable, only needed for "CompatibilityOptions"
 
Double_t fMethodError
 estimation of the level error of the classifier
 
Bool_t fMonitorBoostedMethod
 monitor the MVA response of every classifier
 
TTreefMonitorTree
 tree to monitor values during the boosting
 
std::vector< Float_t > * fMVAvalues
 mva values for the last trained method
 
Double_t fOverlap_integral
 
UInt_t fRandomSeed
 seed for random number generator used for bagging
 
Double_t fROC_training
 roc integral of last trained method (on training sample)
 
std::vector< TH1 * > fTestBgdMVAHist
 
std::vector< TH1 * > fTestSigMVAHist
 
std::vector< TH1 * > fTrainBgdMVAHist
 
std::vector< TH1 * > fTrainSigMVAHist
 
TString fTransformString
 min and max values for the classifier response
 

Friends

class Experimental::Classification
 
class Factory
 
class Reader
 

Additional Inherited Members

- Public Types inherited from TMVA::MethodBase
enum  EWeightFileType { kROOT =0 , kTEXT }
 
- Public Types inherited from TObject
enum  {
  kIsOnHeap = 0x01000000 , kNotDeleted = 0x02000000 , kZombie = 0x04000000 , kInconsistent = 0x08000000 ,
  kBitMask = 0x00ffffff
}
 
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 Attributes inherited from TMVA::MethodBase
Bool_t fSetupCompleted
 
TrainingHistory fTrainHistory
 
- Protected Types inherited from TObject
enum  { kOnlyPrepStep = (1ULL << ( 3 )) }
 
- Protected Attributes inherited from TMVA::MethodCompositeBase
MethodBasefCurrentMethod
 
UInt_t fCurrentMethodIdx
 
std::vector< IMethod * > fMethods
 vector of all classifiers
 
std::vector< Double_tfMethodWeight
 
- Protected Attributes inherited from TMVA::MethodBase
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)
 
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
 
const EventfTmpEvent
 
- Protected Attributes inherited from TMVA::Configurable
MsgLoggerfLogger
 ! message logger
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

#include <TMVA/MethodBoost.h>

Inheritance diagram for TMVA::MethodBoost:
[legend]

Constructor & Destructor Documentation

◆ MethodBoost() [1/2]

TMVA::MethodBoost::MethodBoost ( const TString jobName,
const TString methodTitle,
DataSetInfo theData,
const TString theOption = "" 
)

Definition at line 90 of file MethodBoost.cxx.

◆ MethodBoost() [2/2]

TMVA::MethodBoost::MethodBoost ( DataSetInfo dsi,
const TString theWeightFile 
)

Definition at line 117 of file MethodBoost.cxx.

◆ ~MethodBoost()

TMVA::MethodBoost::~MethodBoost ( void  )
virtual

destructor

Definition at line 143 of file MethodBoost.cxx.

Member Function Documentation

◆ AdaBoost()

Double_t TMVA::MethodBoost::AdaBoost ( MethodBase method,
Bool_t  useYesNoLeaf 
)
private

the standard (discrete or real) AdaBoost algorithm

Definition at line 867 of file MethodBoost.cxx.

◆ Bagging()

Double_t TMVA::MethodBoost::Bagging ( )
private

Bagging or Bootstrap boosting, gives new random poisson weight for every event.

Definition at line 1031 of file MethodBoost.cxx.

◆ BookMethod()

Bool_t TMVA::MethodBoost::BookMethod ( Types::EMVA  theMethod,
TString  methodTitle,
TString  theOption 
)

just registering the string from which the boosted classifier will be created

Definition at line 250 of file MethodBoost.cxx.

◆ CalcMethodWeight()

Double_t TMVA::MethodBoost::CalcMethodWeight ( )
private

◆ CalcMVAValues()

void TMVA::MethodBoost::CalcMVAValues ( )
private

Definition at line 1277 of file MethodBoost.cxx.

◆ CheckSetup()

void TMVA::MethodBoost::CheckSetup ( )
privatevirtual

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

Reimplemented from TMVA::MethodBase.

Definition at line 328 of file MethodBoost.cxx.

◆ Class()

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

◆ Class_Name()

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

◆ Class_Version()

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

Definition at line 202 of file MethodBoost.h.

◆ CleanBoostOptions()

void TMVA::MethodBoost::CleanBoostOptions ( )

Definition at line 531 of file MethodBoost.cxx.

◆ ClearAll()

void TMVA::MethodBoost::ClearAll ( )
private

◆ CreateMVAHistorgrams()

void TMVA::MethodBoost::CreateMVAHistorgrams ( )
private

Definition at line 538 of file MethodBoost.cxx.

◆ CreateRanking()

const TMVA::Ranking * TMVA::MethodBoost::CreateRanking ( )
virtual

Implements TMVA::MethodCompositeBase.

Definition at line 1087 of file MethodBoost.cxx.

◆ CurrentMethod()

MethodBase * TMVA::MethodBoost::CurrentMethod ( )
inlineprivate

Definition at line 114 of file MethodBoost.h.

◆ CurrentMethodIdx()

UInt_t TMVA::MethodBoost::CurrentMethodIdx ( )
inlineprivate

Definition at line 115 of file MethodBoost.h.

◆ DeclareCompatibilityOptions()

void TMVA::MethodBoost::DeclareCompatibilityOptions ( )
privatevirtual

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 from TMVA::MethodBase.

Definition at line 215 of file MethodBoost.cxx.

◆ DeclareOptions()

void TMVA::MethodBoost::DeclareOptions ( )
privatevirtual

Implements TMVA::MethodCompositeBase.

Definition at line 176 of file MethodBoost.cxx.

◆ DeclFileName()

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

Definition at line 202 of file MethodBoost.h.

◆ FindMVACut()

void TMVA::MethodBoost::FindMVACut ( MethodBase method)
private

find the CUT on the individual MVA that defines an event as correct or misclassified (to be used in the boosting process)

Definition at line 690 of file MethodBoost.cxx.

◆ GetBoostNum()

Int_t TMVA::MethodBoost::GetBoostNum ( )
inline

Definition at line 88 of file MethodBoost.h.

◆ GetBoostROCIntegral()

Double_t TMVA::MethodBoost::GetBoostROCIntegral ( Bool_t  singleMethod,
Types::ETreeType  eTT,
Bool_t  CalcOverlapIntergral = kFALSE 
)
private

Calculate the ROC integral of a single classifier or even the whole boosted classifier.

The tree type (training or testing sample) is specified by 'eTT'.

If tree type kTraining is set, the original training sample is used to compute the ROC integral (original weights).

  • singleMethod - if kTRUE, return ROC integral of single (last trained) classifier; if kFALSE, return ROC integral of full classifier
  • eTT - tree type (Types::kTraining / Types::kTesting)
  • CalcOverlapIntergral - if kTRUE, the overlap integral of the signal/background MVA distributions is calculated and stored in 'fOverlap_integral'

Definition at line 1156 of file MethodBoost.cxx.

◆ GetHelpMessage()

void TMVA::MethodBoost::GetHelpMessage ( ) const
protectedvirtual

Get help message text.

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

Implements TMVA::IMethod.

Definition at line 1049 of file MethodBoost.cxx.

◆ GetMvaValue()

Double_t TMVA::MethodBoost::GetMvaValue ( Double_t err = nullptr,
Double_t errUpper = nullptr 
)
virtual

return boosted MVA response

Implements TMVA::MethodBase.

Definition at line 1095 of file MethodBoost.cxx.

◆ HasAnalysisType()

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

Boost can handle classification with 2 classes and regression with one regression-target.

Implements TMVA::IMethod.

Definition at line 166 of file MethodBoost.cxx.

◆ Init()

void TMVA::MethodBoost::Init ( void  )
privatevirtual

Implements TMVA::MethodBase.

Definition at line 264 of file MethodBoost.cxx.

◆ InitHistos()

void TMVA::MethodBoost::InitHistos ( )
private

initialisation routine

Definition at line 271 of file MethodBoost.cxx.

◆ IsA()

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

Reimplemented from TMVA::MethodCompositeBase.

Definition at line 202 of file MethodBoost.h.

◆ MonitorBoost()

void TMVA::MethodBoost::MonitorBoost ( Types::EBoostStage  stage,
UInt_t  methodIndex = 0 
)
private

fill various monitoring histograms from information of the individual classifiers that have been boosted.

of course.... this depends very much on the individual classifiers, and so far, only for Decision Trees, this monitoring is actually implemented

Definition at line 1305 of file MethodBoost.cxx.

◆ PrintResults()

void TMVA::MethodBoost::PrintResults ( const TString ,
std::vector< Double_t > &  ,
const Double_t   
) const
private

◆ ProcessOptions()

void TMVA::MethodBoost::ProcessOptions ( )
privatevirtual

process user options

Implements TMVA::MethodCompositeBase.

Definition at line 663 of file MethodBoost.cxx.

◆ ResetBoostWeights()

void TMVA::MethodBoost::ResetBoostWeights ( )
private

resetting back the boosted weights of the events to 1

Definition at line 569 of file MethodBoost.cxx.

◆ SetBoostedMethodName()

void TMVA::MethodBoost::SetBoostedMethodName ( TString  methodName)
inline

Definition at line 86 of file MethodBoost.h.

◆ SingleBoost()

Double_t TMVA::MethodBoost::SingleBoost ( MethodBase method)
private

Definition at line 850 of file MethodBoost.cxx.

◆ SingleTrain()

void TMVA::MethodBoost::SingleTrain ( )
private

initialization

Definition at line 670 of file MethodBoost.cxx.

◆ Streamer()

virtual void TMVA::MethodBoost::Streamer ( TBuffer )
virtual

Reimplemented from TMVA::MethodCompositeBase.

◆ StreamerNVirtual()

void TMVA::MethodBoost::StreamerNVirtual ( TBuffer ClassDef_StreamerNVirtual_b)
inline

Definition at line 202 of file MethodBoost.h.

◆ TestClassification()

void TMVA::MethodBoost::TestClassification ( )
privatevirtual

initialization

Reimplemented from TMVA::MethodBase.

Definition at line 609 of file MethodBoost.cxx.

◆ Train()

void TMVA::MethodBoost::Train ( void  )
virtual

Implements TMVA::MethodCompositeBase.

Definition at line 351 of file MethodBoost.cxx.

◆ WriteEvaluationHistosToFile()

void TMVA::MethodBoost::WriteEvaluationHistosToFile ( Types::ETreeType  treetype)
privatevirtual

writes all MVA evaluation histograms to file

Reimplemented from TMVA::MethodBase.

Definition at line 637 of file MethodBoost.cxx.

◆ WriteMonitoringHistosToFile()

void TMVA::MethodBoost::WriteMonitoringHistosToFile ( void  ) const
privatevirtual

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

Reimplemented from TMVA::MethodBase.

Definition at line 579 of file MethodBoost.cxx.

Friends And Related Symbol Documentation

◆ Experimental::Classification

friend class Experimental::Classification
friend

Definition at line 61 of file MethodBoost.h.

◆ Factory

friend class Factory
friend

Definition at line 59 of file MethodBoost.h.

◆ Reader

friend class Reader
friend

Definition at line 60 of file MethodBoost.h.

Member Data Documentation

◆ fAdaBoostBeta

Double_t TMVA::MethodBoost::fAdaBoostBeta
private

ADA boost parameter, default is 1.

Definition at line 159 of file MethodBoost.h.

◆ fBaggedSampleFraction

Double_t TMVA::MethodBoost::fBaggedSampleFraction
private

rel.Size of bagged sample

Definition at line 161 of file MethodBoost.h.

◆ fBoostedMethodName

TString TMVA::MethodBoost::fBoostedMethodName
private

details of the boosted classifier

Definition at line 163 of file MethodBoost.h.

◆ fBoostedMethodOptions

TString TMVA::MethodBoost::fBoostedMethodOptions
private

options

Definition at line 165 of file MethodBoost.h.

◆ fBoostedMethodTitle

TString TMVA::MethodBoost::fBoostedMethodTitle
private

title

Definition at line 164 of file MethodBoost.h.

◆ fBoostNum

UInt_t TMVA::MethodBoost::fBoostNum
private

Number of times the classifier is boosted.

Definition at line 153 of file MethodBoost.h.

◆ fBoostType

TString TMVA::MethodBoost::fBoostType
private

string specifying the boost type

Definition at line 154 of file MethodBoost.h.

◆ fBoostWeight

Double_t TMVA::MethodBoost::fBoostWeight
private

the weight used to boost the next classifier

Definition at line 182 of file MethodBoost.h.

◆ fBTrainBgdMVAHist

std::vector< TH1* > TMVA::MethodBoost::fBTrainBgdMVAHist
private

Definition at line 174 of file MethodBoost.h.

◆ fBTrainSigMVAHist

std::vector< TH1* > TMVA::MethodBoost::fBTrainSigMVAHist
private

Definition at line 173 of file MethodBoost.h.

◆ fDataSetManager

DataSetManager* TMVA::MethodBoost::fDataSetManager
private

DSMTEST.

Definition at line 193 of file MethodBoost.h.

◆ fDetailedMonitoring

Bool_t TMVA::MethodBoost::fDetailedMonitoring
private

produce detailed monitoring histograms (boost-wise)

Definition at line 157 of file MethodBoost.h.

◆ fHistoricBoolOption

Bool_t TMVA::MethodBoost::fHistoricBoolOption
private

historic variable, only needed for "CompatibilityOptions"

Definition at line 195 of file MethodBoost.h.

◆ fHistoricOption

TString TMVA::MethodBoost::fHistoricOption
private

historic variable, only needed for "CompatibilityOptions"

Definition at line 194 of file MethodBoost.h.

◆ fMethodError

Double_t TMVA::MethodBoost::fMethodError
private

estimation of the level error of the classifier

Definition at line 183 of file MethodBoost.h.

◆ fMonitorBoostedMethod

Bool_t TMVA::MethodBoost::fMonitorBoostedMethod
private

monitor the MVA response of every classifier

Definition at line 167 of file MethodBoost.h.

◆ fMonitorTree

TTree* TMVA::MethodBoost::fMonitorTree
private

tree to monitor values during the boosting

Definition at line 181 of file MethodBoost.h.

◆ fMVAvalues

std::vector<Float_t>* TMVA::MethodBoost::fMVAvalues
private

mva values for the last trained method

Definition at line 191 of file MethodBoost.h.

◆ fOverlap_integral

Double_t TMVA::MethodBoost::fOverlap_integral
private

Definition at line 189 of file MethodBoost.h.

◆ fRandomSeed

UInt_t TMVA::MethodBoost::fRandomSeed
private

seed for random number generator used for bagging

Definition at line 160 of file MethodBoost.h.

◆ fROC_training

Double_t TMVA::MethodBoost::fROC_training
private

roc integral of last trained method (on training sample)

Definition at line 185 of file MethodBoost.h.

◆ fTestBgdMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTestBgdMVAHist
private

Definition at line 178 of file MethodBoost.h.

◆ fTestSigMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTestSigMVAHist
private

Definition at line 176 of file MethodBoost.h.

◆ fTrainBgdMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTrainBgdMVAHist
private

Definition at line 171 of file MethodBoost.h.

◆ fTrainSigMVAHist

std::vector< TH1* > TMVA::MethodBoost::fTrainSigMVAHist
private

Definition at line 170 of file MethodBoost.h.

◆ fTransformString

TString TMVA::MethodBoost::fTransformString
private

min and max values for the classifier response

Definition at line 156 of file MethodBoost.h.

Libraries for TMVA::MethodBoost:

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