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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 More...
 
Bool_t BookMethod (Types::EMVA theMethod, TString methodTitle, TString theOption)
 just registering the string from which the boosted classifier will be created More...
 
void CleanBoostOptions ()
 
const RankingCreateRanking ()
 
Int_t GetBoostNum ()
 
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
 return boosted MVA response More...
 
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. More...
 
void SetBoostedMethodName (TString methodName)
 
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 More...
 
void AddWeightsXMLTo (void *parent) const
 
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
 return composite MVA response More...
 
void ReadWeightsFromStream (std::istream &istr)
 text streamer More...
 
void ReadWeightsFromXML (void *wghtnode)
 XML streamer. More...
 
- Public Member Functions inherited from TMVA::MethodBase
 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...
 
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. 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=0, Double_t *errUpper=0)
 
const char * GetName () const
 
UInt_t GetNEvents () const
 temporary event when testing on a different DataSet than the own one More...
 
UInt_t GetNTargets () const
 
UInt_t GetNvar () const
 
UInt_t GetNVariables () const
 
virtual Double_t GetProba (const Event *ev)
 
virtual Double_t GetProba (Double_t mvaVal, Double_t ap_sig)
 compute likelihood ratio More...
 
const TString GetProbaName () const
 
virtual Double_t GetRarity (Double_t mvaVal, Types::ESBType reftype=Types::kBackground) const
 compute rarity:

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

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

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

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

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

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

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

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

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

Protected Member Functions

void GetHelpMessage () const
 Get help message text. More...
 
- Protected Member Functions inherited from TMVA::MethodCompositeBase
MethodBaseGetCurrentMethod ()
 
MethodBaseGetCurrentMethod (UInt_t idx)
 
UInt_t GetCurrentMethodIndex ()
 
IMethodGetLastMethod ()
 
IMethodGetMethod (const TString &title) const
 returns pointer to MVA that corresponds to given method title More...
 
IMethodGetMethod (const Int_t index) const
 returns pointer to MVA that corresponds to given method index More...
 
IMethodGetPreviousMethod ()
 
- Protected Member Functions inherited from TMVA::MethodBase
const TStringGetInternalVarName (Int_t ivar) const
 
virtual std::vector< Double_tGetMvaValues (Long64_t firstEvt=0, Long64_t lastEvt=-1, Bool_t logProgress=false)
 get all the MVA values for the events of the current Data type More...
 
const TStringGetOriginalVarName (Int_t ivar) const
 
const TStringGetWeightFileDir () const
 
Bool_t HasTrainingTree () const
 
Bool_t Help () const
 
Bool_t IgnoreEventsWithNegWeightsInTraining () const
 
Bool_t IsConstructedFromWeightFile () const
 
Bool_t IsNormalised () const
 
virtual void MakeClassSpecific (std::ostream &, const TString &="") const
 
virtual void MakeClassSpecificHeader (std::ostream &, const TString &="") const
 
void NoErrorCalc (Double_t *const err, Double_t *const errUpper)
 
virtual void ReadWeightsFromStream (TFile &)
 
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::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 ()
 

Private Member Functions

Double_t AdaBoost (MethodBase *method, Bool_t useYesNoLeaf)
 the standard (discrete or real) AdaBoost algorithm More...
 
Double_t Bagging ()
 Bagging or Bootstrap boosting, gives new random poisson weight for every event. More...
 
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) More...
 
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 More...
 
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) More...
 
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. More...
 
void Init ()
 
void InitHistos ()
 initialisation routine More...
 
void MonitorBoost (Types::EBoostStage stage, UInt_t methodIdx=0)
 fill various monitoring histograms from information of the individual classifiers that have been boosted. More...
 
void PrintResults (const TString &, std::vector< Double_t > &, const Double_t) const
 
void ProcessOptions ()
 process user options More...
 
void ResetBoostWeights ()
 resetting back the boosted weights of the events to 1 More...
 
Double_t SingleBoost (MethodBase *method)
 
void SingleTrain ()
 initialization More...
 
virtual void TestClassification ()
 initialization More...
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file More...
 
void WriteMonitoringHistosToFile (void) const
 write special monitoring histograms to file dummy implementation here --------------— More...
 

Private Attributes

Double_t fAdaBoostBeta
 
Double_t fBaggedSampleFraction
 
TString fBoostedMethodName
 
TString fBoostedMethodOptions
 
TString fBoostedMethodTitle
 
UInt_t fBoostNum
 
TString fBoostType
 
Double_t fBoostWeight
 
std::vector< TH1 *> fBTrainBgdMVAHist
 
std::vector< TH1 *> fBTrainSigMVAHist
 
DataSetManagerfDataSetManager
 
Bool_t fDetailedMonitoring
 
Bool_t fHistoricBoolOption
 
TString fHistoricOption
 
Double_t fMethodError
 
Bool_t fMonitorBoostedMethod
 
TTreefMonitorTree
 
std::vector< Float_t > * fMVAvalues
 
Double_t fOverlap_integral
 
UInt_t fRandomSeed
 
Double_t fROC_training
 
std::vector< TH1 *> fTestBgdMVAHist
 
std::vector< TH1 *> fTestSigMVAHist
 
std::vector< TH1 *> fTrainBgdMVAHist
 
std::vector< TH1 *> fTrainSigMVAHist
 
TString fTransformString
 

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 = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 
enum  EDeprecatedStatusBits { kObjInCanvas = BIT(3) }
 
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kIsReferenced = BIT(4), kHasUUID = BIT(5),
  kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 
- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 
- Public Attributes inherited from TMVA::MethodBase
Bool_t fSetupCompleted
 
const EventfTmpEvent
 
- Protected Attributes inherited from TMVA::MethodCompositeBase
MethodBasefCurrentMethod
 
UInt_t fCurrentMethodIdx
 
std::vector< IMethod * > fMethods
 
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
 
UInt_t fIPyCurrentIter = 0
 
UInt_t fIPyMaxIter = 0
 
std::vector< Float_t > * fMulticlassReturnVal
 
Int_t fNbins
 
Int_t fNbinsH
 
Int_t fNbinsMVAoutput
 
RankingfRanking
 
std::vector< Float_t > * fRegressionReturnVal
 
ResultsfResults
 
UInt_t fSignalClass
 
- Protected Attributes inherited from TMVA::Configurable
MsgLoggerfLogger
 
- Protected Attributes inherited from TNamed
TString fName
 
TString fTitle
 

#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 94 of file MethodBoost.cxx.

◆ MethodBoost() [2/2]

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

Definition at line 121 of file MethodBoost.cxx.

◆ ~MethodBoost()

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

destructor

Definition at line 147 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 874 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 1038 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 254 of file MethodBoost.cxx.

◆ CalcMethodWeight()

Double_t TMVA::MethodBoost::CalcMethodWeight ( )
private

◆ CalcMVAValues()

void TMVA::MethodBoost::CalcMVAValues ( )
private

Definition at line 1284 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 332 of file MethodBoost.cxx.

◆ CleanBoostOptions()

void TMVA::MethodBoost::CleanBoostOptions ( )

Definition at line 535 of file MethodBoost.cxx.

◆ ClearAll()

void TMVA::MethodBoost::ClearAll ( )
private

◆ CreateMVAHistorgrams()

void TMVA::MethodBoost::CreateMVAHistorgrams ( )
private

Definition at line 542 of file MethodBoost.cxx.

◆ CreateRanking()

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

Implements TMVA::MethodCompositeBase.

Definition at line 1094 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 219 of file MethodBoost.cxx.

◆ DeclareOptions()

void TMVA::MethodBoost::DeclareOptions ( )
privatevirtual

Implements TMVA::MethodCompositeBase.

Definition at line 180 of file MethodBoost.cxx.

◆ 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 694 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 1163 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 1056 of file MethodBoost.cxx.

◆ GetMvaValue()

Double_t TMVA::MethodBoost::GetMvaValue ( Double_t err = 0,
Double_t errUpper = 0 
)
virtual

return boosted MVA response

Implements TMVA::MethodBase.

Definition at line 1102 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 170 of file MethodBoost.cxx.

◆ Init()

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

Implements TMVA::MethodBase.

Definition at line 268 of file MethodBoost.cxx.

◆ InitHistos()

void TMVA::MethodBoost::InitHistos ( )
private

initialisation routine

Definition at line 275 of file MethodBoost.cxx.

◆ 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 1312 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 667 of file MethodBoost.cxx.

◆ ResetBoostWeights()

void TMVA::MethodBoost::ResetBoostWeights ( )
private

resetting back the boosted weights of the events to 1

Definition at line 573 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 857 of file MethodBoost.cxx.

◆ SingleTrain()

void TMVA::MethodBoost::SingleTrain ( )
private

initialization

Definition at line 674 of file MethodBoost.cxx.

◆ TestClassification()

void TMVA::MethodBoost::TestClassification ( )
privatevirtual

initialization

Reimplemented from TMVA::MethodBase.

Definition at line 613 of file MethodBoost.cxx.

◆ Train()

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

Implements TMVA::MethodCompositeBase.

Definition at line 355 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 641 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 583 of file MethodBoost.cxx.

Friends And Related Function 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

Definition at line 159 of file MethodBoost.h.

◆ fBaggedSampleFraction

Double_t TMVA::MethodBoost::fBaggedSampleFraction
private

Definition at line 161 of file MethodBoost.h.

◆ fBoostedMethodName

TString TMVA::MethodBoost::fBoostedMethodName
private

Definition at line 163 of file MethodBoost.h.

◆ fBoostedMethodOptions

TString TMVA::MethodBoost::fBoostedMethodOptions
private

Definition at line 165 of file MethodBoost.h.

◆ fBoostedMethodTitle

TString TMVA::MethodBoost::fBoostedMethodTitle
private

Definition at line 164 of file MethodBoost.h.

◆ fBoostNum

UInt_t TMVA::MethodBoost::fBoostNum
private

Definition at line 153 of file MethodBoost.h.

◆ fBoostType

TString TMVA::MethodBoost::fBoostType
private

Definition at line 154 of file MethodBoost.h.

◆ fBoostWeight

Double_t TMVA::MethodBoost::fBoostWeight
private

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

Definition at line 193 of file MethodBoost.h.

◆ fDetailedMonitoring

Bool_t TMVA::MethodBoost::fDetailedMonitoring
private

Definition at line 157 of file MethodBoost.h.

◆ fHistoricBoolOption

Bool_t TMVA::MethodBoost::fHistoricBoolOption
private

Definition at line 195 of file MethodBoost.h.

◆ fHistoricOption

TString TMVA::MethodBoost::fHistoricOption
private

Definition at line 194 of file MethodBoost.h.

◆ fMethodError

Double_t TMVA::MethodBoost::fMethodError
private

Definition at line 183 of file MethodBoost.h.

◆ fMonitorBoostedMethod

Bool_t TMVA::MethodBoost::fMonitorBoostedMethod
private

Definition at line 167 of file MethodBoost.h.

◆ fMonitorTree

TTree* TMVA::MethodBoost::fMonitorTree
private

Definition at line 181 of file MethodBoost.h.

◆ fMVAvalues

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

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

Definition at line 160 of file MethodBoost.h.

◆ fROC_training

Double_t TMVA::MethodBoost::fROC_training
private

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

Definition at line 156 of file MethodBoost.h.

Libraries for TMVA::MethodBoost:
[legend]

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