Logo ROOT   6.21/01
Reference Guide
TMVA::MethodRuleFit Class Reference

J Friedman's RuleFit method.

Definition at line 47 of file MethodRuleFit.h.

Public Member Functions

 MethodRuleFit (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="")
 standard constructor More...
 
 MethodRuleFit (DataSetInfo &theData, const TString &theWeightFile)
 constructor from weight file More...
 
virtual ~MethodRuleFit (void)
 destructor More...
 
void AddWeightsXMLTo (void *parent) const
 add the rules to XML node More...
 
const RankingCreateRanking ()
 computes ranking of input variables More...
 
const std::vector< TMVA::DecisionTree * > & GetForest () const
 
Double_t GetGDErrScale () const
 
Int_t GetGDNPathSteps () const
 
Double_t GetGDPathEveFrac () const
 
Double_t GetGDPathStep () const
 
Double_t GetGDValidEveFrac () const
 
Double_t GetLinQuantile () const
 
Double_t GetMaxFracNEve () const
 
TDirectoryGetMethodBaseDir () const
 
Double_t GetMinFracNEve () const
 
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
 returns MVA value for given event More...
 
Int_t GetNCuts () const
 
Int_t GetNTrees () const
 
TMVA::DecisionTree::EPruneMethod GetPruneMethod () const
 
Double_t GetPruneStrength () const
 
Int_t GetRFNendnodes () const
 
Int_t GetRFNrules () const
 
const TString GetRFWorkDir () const
 
const RuleFitGetRuleFitConstPtr () const
 
RuleFitGetRuleFitPtr ()
 
SeparationBaseGetSeparationBase () const
 
const SeparationBaseGetSeparationBaseConst () const
 
const std::vector< TMVA::Event * > & GetTrainingEvents () const
 
Double_t GetTreeEveFrac () const
 
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t)
 RuleFit can handle classification with 2 classes. More...
 
virtual void ReadWeightsFromStream (TFile &)
 
virtual void ReadWeightsFromStream (std::istream &)=0
 
void ReadWeightsFromStream (std::istream &istr)
 read rules from an std::istream More...
 
void ReadWeightsFromXML (void *wghtnode)
 read rules from XML node More...
 
void Train (void)
 
Bool_t UseBoost () const
 
void WriteMonitoringHistosToFile (void) const
 write special monitoring histograms to file (here ntuple) 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...
 
virtual void CheckSetup ()
 check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
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...
 
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
 
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
 
void InitIPythonInteractive ()
 
Bool_t IsModelPersistence () const
 
virtual Bool_t IsSignalLike ()
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event would be selected as signal or background More...
 
virtual Bool_t IsSignalLike (Double_t mvaVal)
 uses a pre-set cut on the MVA output (SetSignalReferenceCut and SetSignalReferenceCutOrientation) for a quick determination if an event with this mva output value would be selected as signal or background More...
 
Bool_t IsSilentFile () const
 
virtual void MakeClass (const TString &classFileName=TString("")) const
 create reader class for method (classification only at present) More...
 
TDirectoryMethodBaseDir () const
 returns the ROOT directory where all instances of the corresponding MVA method are stored More...
 
virtual std::map< TString, Double_tOptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
 call the Optimizer with the set of parameters and ranges that are meant to be tuned. More...
 
void PrintHelpMessage () const
 prints out method-specific help method More...
 
void ProcessSetup ()
 process all options the "CheckForUnusedOptions" is done in an independent call, since it may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
void ReadStateFromFile ()
 Function to write options and weights to file. More...
 
void ReadStateFromStream (std::istream &tf)
 read the header from the weight files of the different MVA methods More...
 
void ReadStateFromStream (TFile &rf)
 write reference MVA distributions (and other information) to a ROOT type weight file More...
 
void ReadStateFromXMLString (const char *xmlstr)
 for reading from memory More...
 
void RerouteTransformationHandler (TransformationHandler *fTargetTransformation)
 
virtual void Reset ()
 
virtual void SetAnalysisType (Types::EAnalysisType type)
 
void SetBaseDir (TDirectory *methodDir)
 
void SetFile (TFile *file)
 
void SetMethodBaseDir (TDirectory *methodDir)
 
void SetMethodDir (TDirectory *methodDir)
 
void SetModelPersistence (Bool_t status)
 
void SetSignalReferenceCut (Double_t cut)
 
void SetSignalReferenceCutOrientation (Double_t cutOrientation)
 
void SetSilentFile (Bool_t status)
 
void SetTestTime (Double_t testTime)
 
void SetTestvarName (const TString &v="")
 
void SetTrainTime (Double_t trainTime)
 
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
 set the tuning parameters according to the argument This is just a dummy . More...
 
void SetupMethod ()
 setup of methods More...
 
virtual void TestClassification ()
 initialization More...
 
virtual void TestMulticlass ()
 test multiclass classification More...
 
virtual void TestRegression (Double_t &bias, Double_t &biasT, Double_t &dev, Double_t &devT, Double_t &rms, Double_t &rmsT, Double_t &mInf, Double_t &mInfT, Double_t &corr, Types::ETreeType type)
 calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample More...
 
bool TrainingEnded ()
 
void TrainMethod ()
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file 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 ()
 
- Public Member Functions inherited from TMVA::Configurable
 Configurable (const TString &theOption="")
 constructor More...
 
virtual ~Configurable ()
 default destructor More...
 
void AddOptionsXMLTo (void *parent) const
 write options to XML file More...
 
template<class T >
void AddPreDefVal (const T &)
 
template<class T >
void AddPreDefVal (const TString &optname, const T &)
 
void CheckForUnusedOptions () const
 checks for unused options in option string More...
 
template<class T >
OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc="")
 
template<class T >
OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc="")
 
template<class T >
TMVA::OptionBaseDeclareOptionRef (T &ref, const TString &name, const TString &desc)
 
template<class T >
TMVA::OptionBaseDeclareOptionRef (T *&ref, Int_t size, const TString &name, const TString &desc)
 
const char * GetConfigDescription () const
 
const char * GetConfigName () const
 
const TStringGetOptions () const
 
MsgLoggerLog () const
 
virtual void ParseOptions ()
 options parser More...
 
void PrintOptions () const
 prints out the options set in the options string and the defaults More...
 
void ReadOptionsFromStream (std::istream &istr)
 read option back from the weight file More...
 
void ReadOptionsFromXML (void *node)
 
void SetConfigDescription (const char *d)
 
void SetConfigName (const char *n)
 
void SetMsgType (EMsgType t)
 
void SetOptions (const TString &s)
 
void WriteOptionsToStream (std::ostream &o, const TString &prefix) const
 write options to output stream (e.g. in writing the MVA weight files More...
 
- Public Member Functions inherited from TNamed
 TNamed ()
 
 TNamed (const char *name, const char *title)
 
 TNamed (const TString &name, const TString &title)
 
 TNamed (const TNamed &named)
 TNamed copy ctor. More...
 
virtual ~TNamed ()
 TNamed destructor. More...
 
virtual void Clear (Option_t *option="")
 Set name and title to empty strings (""). More...
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility. More...
 
virtual Int_t Compare (const TObject *obj) const
 Compare two TNamed objects. More...
 
virtual void Copy (TObject &named) const
 Copy this to obj. More...
 
virtual void FillBuffer (char *&buffer)
 Encode TNamed into output buffer. More...
 
virtual const char * GetTitle () const
 Returns title of object. More...
 
virtual ULong_t Hash () const
 Return hash value for this object. More...
 
virtual Bool_t IsSortable () const
 
virtual void ls (Option_t *option="") const
 List TNamed name and title. More...
 
TNamedoperator= (const TNamed &rhs)
 TNamed assignment operator. More...
 
virtual void Print (Option_t *option="") const
 Print TNamed name and title. More...
 
virtual void SetName (const char *name)
 Set the name of the TNamed. More...
 
virtual void SetNameTitle (const char *name, const char *title)
 Set all the TNamed parameters (name and title). More...
 
virtual void SetTitle (const char *title="")
 Set the title of the TNamed. More...
 
virtual Int_t Sizeof () const
 Return size of the TNamed part of the TObject. More...
 
- Public Member Functions inherited from TObject
 TObject ()
 TObject constructor. More...
 
 TObject (const TObject &object)
 TObject copy ctor. More...
 
virtual ~TObject ()
 TObject destructor. More...
 
void AbstractMethod (const char *method) const
 Use this method to implement an "abstract" method that you don't want to leave purely abstract. More...
 
virtual void AppendPad (Option_t *option="")
 Append graphics object to current pad. More...
 
virtual void Browse (TBrowser *b)
 Browse object. May be overridden for another default action. More...
 
ULong_t CheckedHash ()
 Check and record whether this class has a consistent Hash/RecursiveRemove setup (*) and then return the regular Hash value for this object. More...
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs. More...
 
virtual void Delete (Option_t *option="")
 Delete this object. More...
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object. More...
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects. More...
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs. More...
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current selected pad for instance with: gROOT->SetSelectedPad(gPad). More...
 
virtual void Dump () const
 Dump contents of object on stdout. More...
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message. More...
 
virtual void Execute (const char *method, const char *params, Int_t *error=0)
 Execute method on this object with the given parameter string, e.g. More...
 
virtual void Execute (TMethod *method, TObjArray *params, Int_t *error=0)
 Execute method on this object with parameters stored in the TObjArray. More...
 
virtual void ExecuteEvent (Int_t event, Int_t px, Int_t py)
 Execute action corresponding to an event at (px,py). More...
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message. More...
 
virtual TObjectFindObject (const char *name) const
 Must be redefined in derived classes. More...
 
virtual TObjectFindObject (const TObject *obj) const
 Must be redefined in derived classes. More...
 
virtual Option_tGetDrawOption () const
 Get option used by the graphics system to draw this object. More...
 
virtual const char * GetIconName () const
 Returns mime type name of object. More...
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py). More...
 
virtual Option_tGetOption () const
 
virtual UInt_t GetUniqueID () const
 Return the unique object id. More...
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out. More...
 
Bool_t HasInconsistentHash () const
 Return true is the type of this object is known to have an inconsistent setup for Hash and RecursiveRemove (i.e. More...
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message. More...
 
virtual Bool_t InheritsFrom (const char *classname) const
 Returns kTRUE if object inherits from class "classname". More...
 
virtual Bool_t InheritsFrom (const TClass *cl) const
 Returns kTRUE if object inherits from TClass cl. More...
 
virtual void Inspect () const
 Dump contents of this object in a graphics canvas. More...
 
void InvertBit (UInt_t f)
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory). More...
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...
 
R__ALWAYS_INLINE Bool_t IsOnHeap () const
 
R__ALWAYS_INLINE Bool_t IsZombie () const
 
void MayNotUse (const char *method) const
 Use this method to signal that a method (defined in a base class) may not be called in a derived class (in principle against good design since a child class should not provide less functionality than its parent, however, sometimes it is necessary). More...
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification. More...
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete. More...
 
void operator delete (void *ptr)
 Operator delete. More...
 
void operator delete[] (void *ptr)
 Operator delete []. More...
 
voidoperator new (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz)
 
voidoperator new[] (size_t sz, void *vp)
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator. More...
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself. More...
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list. More...
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory. More...
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list. More...
 
void ResetBit (UInt_t f)
 
virtual void SaveAs (const char *filename="", Option_t *option="") const
 Save this object in the file specified by filename. More...
 
virtual void SavePrimitive (std::ostream &out, Option_t *option="")
 Save a primitive as a C++ statement(s) on output stream "out". More...
 
void SetBit (UInt_t f, Bool_t set)
 Set or unset the user status bits as specified in f. More...
 
void SetBit (UInt_t f)
 
virtual void SetDrawOption (Option_t *option="")
 Set drawing option for object. More...
 
virtual void SetUniqueID (UInt_t uid)
 Set the unique object id. More...
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message. More...
 
R__ALWAYS_INLINE Bool_t TestBit (UInt_t f) const
 
Int_t TestBits (UInt_t f) const
 
virtual void UseCurrentStyle ()
 Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. More...
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0)
 Write this object to the current directory. More...
 
virtual Int_t Write (const char *name=0, Int_t option=0, Int_t bufsize=0) const
 Write this object to the current directory. More...
 

Protected Member Functions

void GetHelpMessage () const
 get help message text More...
 
void Init (void)
 default initialization More...
 
void InitEventSample (void)
 write all Events from the Tree into a vector of Events, that are more easily manipulated. More...
 
void InitMonitorNtuple ()
 initialize the monitoring ntuple More...
 
void MakeClassLinear (std::ostream &) const
 print out the linear terms More...
 
void MakeClassRuleCuts (std::ostream &) const
 print out the rule cuts More...
 
void MakeClassSpecific (std::ostream &, const TString &) const
 write specific classifier response More...
 
void TrainJFRuleFit ()
 training of rules using Jerome Friedmans implementation More...
 
void TrainTMVARuleFit ()
 training of rules using TMVA implementation More...
 
- 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 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

void DeclareOptions ()
 define the options (their key words) that can be set in the option string know options. More...
 
void ProcessOptions ()
 process the options specified by the user More...
 
template<typename T >
Bool_t VerifyRange (MsgLogger &mlog, const char *varstr, T &var, const T &vmin, const T &vmax)
 
template<typename T >
Bool_t VerifyRange (MsgLogger &mlog, const char *varstr, T &var, const T &vmin, const T &vmax, const T &vdef)
 
template<typename T >
Int_t VerifyRange (const T &var, const T &vmin, const T &vmax)
 

Private Attributes

std::vector< TMVA::Event * > fEventSample
 
std::vector< DecisionTree * > fForest
 
TString fForestTypeS
 
Double_t fGDErrScale
 
Int_t fGDNPathSteps
 
Double_t fGDPathEveFrac
 
Double_t fGDPathStep
 
Double_t fGDTau
 
Double_t fGDTauMax
 
Double_t fGDTauMin
 
Double_t fGDTauPrec
 
UInt_t fGDTauScan
 
Double_t fGDValidEveFrac
 
Double_t fLinQuantile
 
Double_t fMaxFracNEve
 
Double_t fMinFracNEve
 
Double_t fMinimp
 
TString fModelTypeS
 
TTreefMonitorNtuple
 
Int_t fNCuts
 
Double_t fNTCoefficient
 
Double_t fNTImportance
 
Int_t fNTNcuts
 
Int_t fNTNvars
 
Double_t fNTPbb
 
Double_t fNTPbs
 
Double_t fNTPsb
 
Double_t fNTPss
 
Double_t fNTPtag
 
Int_t fNTrees
 
Double_t fNTSSB
 
Double_t fNTSupport
 
Int_t fNTType
 
TMVA::DecisionTree::EPruneMethod fPruneMethod
 
TString fPruneMethodS
 
Double_t fPruneStrength
 
Int_t fRFNendnodes
 
Int_t fRFNrules
 
TString fRFWorkDir
 
RuleFit fRuleFit
 
TString fRuleFitModuleS
 
Double_t fRuleMinDist
 
SeparationBasefSepType
 
TString fSepTypeS
 
Double_t fSignalFraction
 
Double_t fTreeEveFrac
 
Bool_t fUseBoost
 
Bool_t fUseRuleFitJF
 

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
 
TrainingHistory fTrainHistory
 
- 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/MethodRuleFit.h>

Inheritance diagram for TMVA::MethodRuleFit:
[legend]

Constructor & Destructor Documentation

◆ MethodRuleFit() [1/2]

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

standard constructor

Definition at line 71 of file MethodRuleFit.cxx.

◆ MethodRuleFit() [2/2]

TMVA::MethodRuleFit::MethodRuleFit ( DataSetInfo theData,
const TString theWeightFile 
)

constructor from weight file

Definition at line 121 of file MethodRuleFit.cxx.

◆ ~MethodRuleFit()

TMVA::MethodRuleFit::~MethodRuleFit ( void  )
virtual

destructor

Definition at line 169 of file MethodRuleFit.cxx.

Member Function Documentation

◆ AddWeightsXMLTo()

void TMVA::MethodRuleFit::AddWeightsXMLTo ( void parent) const
virtual

add the rules to XML node

Implements TMVA::MethodBase.

Definition at line 594 of file MethodRuleFit.cxx.

◆ CreateRanking()

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

computes ranking of input variables

Implements TMVA::MethodBase.

Definition at line 579 of file MethodRuleFit.cxx.

◆ DeclareOptions()

void TMVA::MethodRuleFit::DeclareOptions ( )
privatevirtual

define the options (their key words) that can be set in the option string know options.

general

  • RuleFitModule <string> available values are:
    • RFTMVA - use TMVA implementation
    • RFFriedman - use Friedmans original implementation

Path search (fitting)

  • GDTau <float> gradient-directed path: fit threshold, default
  • GDTauPrec <float> gradient-directed path: precision of estimated tau
  • GDStep <float> gradient-directed path: step size
  • GDNSteps <float> gradient-directed path: number of steps
  • GDErrScale <float> stop scan when error>scale*errmin

Tree generation

  • fEventsMin <float> minimum fraction of events in a splittable node
  • fEventsMax <float> maximum fraction of events in a splittable node
  • nTrees <float> number of trees in forest.
  • ForestType <string> available values are:
    • Random - create forest using random subsample and only random variables subset at each node
    • AdaBoost - create forest with boosted events

Model creation

  • RuleMinDist <float> min distance allowed between rules
  • MinImp <float> minimum rule importance accepted
  • Model <string> model to be used available values are:
    • ModRuleLinear <default>
    • ModRule
    • ModLinear

Friedmans module

  • RFWorkDir <string> directory where Friedmans module (rf_go.exe) is installed
  • RFNrules <int> maximum number of rules allowed
  • RFNendnodes <int> average number of end nodes in the forest of trees

Implements TMVA::MethodBase.

Definition at line 229 of file MethodRuleFit.cxx.

◆ GetForest()

const std::vector<TMVA::DecisionTree*>& TMVA::MethodRuleFit::GetForest ( ) const
inline

Definition at line 91 of file MethodRuleFit.h.

◆ GetGDErrScale()

Double_t TMVA::MethodRuleFit::GetGDErrScale ( ) const
inline

Definition at line 104 of file MethodRuleFit.h.

◆ GetGDNPathSteps()

Int_t TMVA::MethodRuleFit::GetGDNPathSteps ( ) const
inline

Definition at line 102 of file MethodRuleFit.h.

◆ GetGDPathEveFrac()

Double_t TMVA::MethodRuleFit::GetGDPathEveFrac ( ) const
inline

Definition at line 105 of file MethodRuleFit.h.

◆ GetGDPathStep()

Double_t TMVA::MethodRuleFit::GetGDPathStep ( ) const
inline

Definition at line 103 of file MethodRuleFit.h.

◆ GetGDValidEveFrac()

Double_t TMVA::MethodRuleFit::GetGDValidEveFrac ( ) const
inline

Definition at line 106 of file MethodRuleFit.h.

◆ GetHelpMessage()

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

get help message text

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

Implements TMVA::IMethod.

Definition at line 752 of file MethodRuleFit.cxx.

◆ GetLinQuantile()

Double_t TMVA::MethodRuleFit::GetLinQuantile ( ) const
inline

Definition at line 108 of file MethodRuleFit.h.

◆ GetMaxFracNEve()

Double_t TMVA::MethodRuleFit::GetMaxFracNEve ( ) const
inline

Definition at line 99 of file MethodRuleFit.h.

◆ GetMethodBaseDir()

TDirectory* TMVA::MethodRuleFit::GetMethodBaseDir ( ) const
inline

Definition at line 89 of file MethodRuleFit.h.

◆ GetMinFracNEve()

Double_t TMVA::MethodRuleFit::GetMinFracNEve ( ) const
inline

Definition at line 98 of file MethodRuleFit.h.

◆ GetMvaValue()

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

returns MVA value for given event

Implements TMVA::MethodBase.

Definition at line 618 of file MethodRuleFit.cxx.

◆ GetNCuts()

Int_t TMVA::MethodRuleFit::GetNCuts ( ) const
inline

Definition at line 100 of file MethodRuleFit.h.

◆ GetNTrees()

Int_t TMVA::MethodRuleFit::GetNTrees ( ) const
inline

Definition at line 92 of file MethodRuleFit.h.

◆ GetPruneMethod()

TMVA::DecisionTree::EPruneMethod TMVA::MethodRuleFit::GetPruneMethod ( ) const
inline

Definition at line 96 of file MethodRuleFit.h.

◆ GetPruneStrength()

Double_t TMVA::MethodRuleFit::GetPruneStrength ( ) const
inline

Definition at line 97 of file MethodRuleFit.h.

◆ GetRFNendnodes()

Int_t TMVA::MethodRuleFit::GetRFNendnodes ( ) const
inline

Definition at line 112 of file MethodRuleFit.h.

◆ GetRFNrules()

Int_t TMVA::MethodRuleFit::GetRFNrules ( ) const
inline

Definition at line 111 of file MethodRuleFit.h.

◆ GetRFWorkDir()

const TString TMVA::MethodRuleFit::GetRFWorkDir ( ) const
inline

Definition at line 110 of file MethodRuleFit.h.

◆ GetRuleFitConstPtr()

const RuleFit* TMVA::MethodRuleFit::GetRuleFitConstPtr ( ) const
inline

Definition at line 88 of file MethodRuleFit.h.

◆ GetRuleFitPtr()

RuleFit* TMVA::MethodRuleFit::GetRuleFitPtr ( )
inline

Definition at line 87 of file MethodRuleFit.h.

◆ GetSeparationBase()

SeparationBase* TMVA::MethodRuleFit::GetSeparationBase ( ) const
inline

Definition at line 95 of file MethodRuleFit.h.

◆ GetSeparationBaseConst()

const SeparationBase* TMVA::MethodRuleFit::GetSeparationBaseConst ( ) const
inline

Definition at line 94 of file MethodRuleFit.h.

◆ GetTrainingEvents()

const std::vector<TMVA::Event*>& TMVA::MethodRuleFit::GetTrainingEvents ( ) const
inline

Definition at line 90 of file MethodRuleFit.h.

◆ GetTreeEveFrac()

Double_t TMVA::MethodRuleFit::GetTreeEveFrac ( ) const
inline

Definition at line 93 of file MethodRuleFit.h.

◆ HasAnalysisType()

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

RuleFit can handle classification with 2 classes.

Implements TMVA::IMethod.

Definition at line 178 of file MethodRuleFit.cxx.

◆ Init()

void TMVA::MethodRuleFit::Init ( void  )
protectedvirtual

default initialization

Implements TMVA::MethodBase.

Definition at line 397 of file MethodRuleFit.cxx.

◆ InitEventSample()

void TMVA::MethodRuleFit::InitEventSample ( void  )
protected

write all Events from the Tree into a vector of Events, that are more easily manipulated.

This method should never be called without existing trainingTree, as it the vector of events from the ROOT training tree

Definition at line 422 of file MethodRuleFit.cxx.

◆ InitMonitorNtuple()

void TMVA::MethodRuleFit::InitMonitorNtuple ( )
protected

initialize the monitoring ntuple

Definition at line 376 of file MethodRuleFit.cxx.

◆ MakeClassLinear()

void TMVA::MethodRuleFit::MakeClassLinear ( std::ostream &  fout) const
protected

print out the linear terms

Definition at line 716 of file MethodRuleFit.cxx.

◆ MakeClassRuleCuts()

void TMVA::MethodRuleFit::MakeClassRuleCuts ( std::ostream &  fout) const
protected

print out the rule cuts

Definition at line 658 of file MethodRuleFit.cxx.

◆ MakeClassSpecific()

void TMVA::MethodRuleFit::MakeClassSpecific ( std::ostream &  fout,
const TString className 
) const
protectedvirtual

write specific classifier response

Reimplemented from TMVA::MethodBase.

Definition at line 639 of file MethodRuleFit.cxx.

◆ ProcessOptions()

void TMVA::MethodRuleFit::ProcessOptions ( )
privatevirtual

process the options specified by the user

Implements TMVA::MethodBase.

Definition at line 267 of file MethodRuleFit.cxx.

◆ ReadWeightsFromStream() [1/3]

virtual void TMVA::MethodBase::ReadWeightsFromStream

◆ ReadWeightsFromStream() [2/3]

virtual void TMVA::MethodBase::ReadWeightsFromStream
inline

Definition at line 265 of file MethodBase.h.

◆ ReadWeightsFromStream() [3/3]

void TMVA::MethodRuleFit::ReadWeightsFromStream ( std::istream &  istr)
virtual

read rules from an std::istream

Implements TMVA::MethodBase.

Definition at line 602 of file MethodRuleFit.cxx.

◆ ReadWeightsFromXML()

void TMVA::MethodRuleFit::ReadWeightsFromXML ( void wghtnode)
virtual

read rules from XML node

Implements TMVA::MethodBase.

Definition at line 610 of file MethodRuleFit.cxx.

◆ Train()

void TMVA::MethodRuleFit::Train ( void  )
virtual

Implements TMVA::MethodBase.

Definition at line 444 of file MethodRuleFit.cxx.

◆ TrainJFRuleFit()

void TMVA::MethodRuleFit::TrainJFRuleFit ( void  )
protected

training of rules using Jerome Friedmans implementation

Definition at line 536 of file MethodRuleFit.cxx.

◆ TrainTMVARuleFit()

void TMVA::MethodRuleFit::TrainTMVARuleFit ( void  )
protected

training of rules using TMVA implementation

Definition at line 468 of file MethodRuleFit.cxx.

◆ UseBoost()

Bool_t TMVA::MethodRuleFit::UseBoost ( ) const
inline

Definition at line 84 of file MethodRuleFit.h.

◆ VerifyRange() [1/3]

template<typename T >
Bool_t TMVA::MethodRuleFit::VerifyRange ( TMVA::MsgLogger mlog,
const char *  varstr,
T &  var,
const T &  vmin,
const T &  vmax 
)
inlineprivate

Definition at line 227 of file MethodRuleFit.h.

◆ VerifyRange() [2/3]

template<typename T >
Bool_t TMVA::MethodRuleFit::VerifyRange ( TMVA::MsgLogger mlog,
const char *  varstr,
T &  var,
const T &  vmin,
const T &  vmax,
const T &  vdef 
)
inlineprivate

Definition at line 249 of file MethodRuleFit.h.

◆ VerifyRange() [3/3]

template<typename T >
Int_t TMVA::MethodRuleFit::VerifyRange ( const T &  var,
const T &  vmin,
const T &  vmax 
)
inlineprivate

Definition at line 217 of file MethodRuleFit.h.

◆ WriteMonitoringHistosToFile()

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

write special monitoring histograms to file (here ntuple)

Reimplemented from TMVA::MethodBase.

Definition at line 629 of file MethodRuleFit.cxx.

Member Data Documentation

◆ fEventSample

std::vector<TMVA::Event *> TMVA::MethodRuleFit::fEventSample
private

Definition at line 155 of file MethodRuleFit.h.

◆ fForest

std::vector<DecisionTree *> TMVA::MethodRuleFit::fForest
private

Definition at line 179 of file MethodRuleFit.h.

◆ fForestTypeS

TString TMVA::MethodRuleFit::fForestTypeS
private

Definition at line 190 of file MethodRuleFit.h.

◆ fGDErrScale

Double_t TMVA::MethodRuleFit::fGDErrScale
private

Definition at line 202 of file MethodRuleFit.h.

◆ fGDNPathSteps

Int_t TMVA::MethodRuleFit::fGDNPathSteps
private

Definition at line 201 of file MethodRuleFit.h.

◆ fGDPathEveFrac

Double_t TMVA::MethodRuleFit::fGDPathEveFrac
private

Definition at line 193 of file MethodRuleFit.h.

◆ fGDPathStep

Double_t TMVA::MethodRuleFit::fGDPathStep
private

Definition at line 200 of file MethodRuleFit.h.

◆ fGDTau

Double_t TMVA::MethodRuleFit::fGDTau
private

Definition at line 195 of file MethodRuleFit.h.

◆ fGDTauMax

Double_t TMVA::MethodRuleFit::fGDTauMax
private

Definition at line 198 of file MethodRuleFit.h.

◆ fGDTauMin

Double_t TMVA::MethodRuleFit::fGDTauMin
private

Definition at line 197 of file MethodRuleFit.h.

◆ fGDTauPrec

Double_t TMVA::MethodRuleFit::fGDTauPrec
private

Definition at line 196 of file MethodRuleFit.h.

◆ fGDTauScan

UInt_t TMVA::MethodRuleFit::fGDTauScan
private

Definition at line 199 of file MethodRuleFit.h.

◆ fGDValidEveFrac

Double_t TMVA::MethodRuleFit::fGDValidEveFrac
private

Definition at line 194 of file MethodRuleFit.h.

◆ fLinQuantile

Double_t TMVA::MethodRuleFit::fLinQuantile
private

Definition at line 207 of file MethodRuleFit.h.

◆ fMaxFracNEve

Double_t TMVA::MethodRuleFit::fMaxFracNEve
private

Definition at line 184 of file MethodRuleFit.h.

◆ fMinFracNEve

Double_t TMVA::MethodRuleFit::fMinFracNEve
private

Definition at line 183 of file MethodRuleFit.h.

◆ fMinimp

Double_t TMVA::MethodRuleFit::fMinimp
private

Definition at line 203 of file MethodRuleFit.h.

◆ fModelTypeS

TString TMVA::MethodRuleFit::fModelTypeS
private

Definition at line 205 of file MethodRuleFit.h.

◆ fMonitorNtuple

TTree* TMVA::MethodRuleFit::fMonitorNtuple
private

Definition at line 159 of file MethodRuleFit.h.

◆ fNCuts

Int_t TMVA::MethodRuleFit::fNCuts
private

Definition at line 185 of file MethodRuleFit.h.

◆ fNTCoefficient

Double_t TMVA::MethodRuleFit::fNTCoefficient
private

Definition at line 161 of file MethodRuleFit.h.

◆ fNTImportance

Double_t TMVA::MethodRuleFit::fNTImportance
private

Definition at line 160 of file MethodRuleFit.h.

◆ fNTNcuts

Int_t TMVA::MethodRuleFit::fNTNcuts
private

Definition at line 163 of file MethodRuleFit.h.

◆ fNTNvars

Int_t TMVA::MethodRuleFit::fNTNvars
private

Definition at line 164 of file MethodRuleFit.h.

◆ fNTPbb

Double_t TMVA::MethodRuleFit::fNTPbb
private

Definition at line 169 of file MethodRuleFit.h.

◆ fNTPbs

Double_t TMVA::MethodRuleFit::fNTPbs
private

Definition at line 168 of file MethodRuleFit.h.

◆ fNTPsb

Double_t TMVA::MethodRuleFit::fNTPsb
private

Definition at line 167 of file MethodRuleFit.h.

◆ fNTPss

Double_t TMVA::MethodRuleFit::fNTPss
private

Definition at line 166 of file MethodRuleFit.h.

◆ fNTPtag

Double_t TMVA::MethodRuleFit::fNTPtag
private

Definition at line 165 of file MethodRuleFit.h.

◆ fNTrees

Int_t TMVA::MethodRuleFit::fNTrees
private

Definition at line 180 of file MethodRuleFit.h.

◆ fNTSSB

Double_t TMVA::MethodRuleFit::fNTSSB
private

Definition at line 170 of file MethodRuleFit.h.

◆ fNTSupport

Double_t TMVA::MethodRuleFit::fNTSupport
private

Definition at line 162 of file MethodRuleFit.h.

◆ fNTType

Int_t TMVA::MethodRuleFit::fNTType
private

Definition at line 171 of file MethodRuleFit.h.

◆ fPruneMethod

TMVA::DecisionTree::EPruneMethod TMVA::MethodRuleFit::fPruneMethod
private

Definition at line 188 of file MethodRuleFit.h.

◆ fPruneMethodS

TString TMVA::MethodRuleFit::fPruneMethodS
private

Definition at line 187 of file MethodRuleFit.h.

◆ fPruneStrength

Double_t TMVA::MethodRuleFit::fPruneStrength
private

Definition at line 189 of file MethodRuleFit.h.

◆ fRFNendnodes

Int_t TMVA::MethodRuleFit::fRFNendnodes
private

Definition at line 178 of file MethodRuleFit.h.

◆ fRFNrules

Int_t TMVA::MethodRuleFit::fRFNrules
private

Definition at line 177 of file MethodRuleFit.h.

◆ fRFWorkDir

TString TMVA::MethodRuleFit::fRFWorkDir
private

Definition at line 176 of file MethodRuleFit.h.

◆ fRuleFit

RuleFit TMVA::MethodRuleFit::fRuleFit
private

Definition at line 154 of file MethodRuleFit.h.

◆ fRuleFitModuleS

TString TMVA::MethodRuleFit::fRuleFitModuleS
private

Definition at line 174 of file MethodRuleFit.h.

◆ fRuleMinDist

Double_t TMVA::MethodRuleFit::fRuleMinDist
private

Definition at line 206 of file MethodRuleFit.h.

◆ fSepType

SeparationBase* TMVA::MethodRuleFit::fSepType
private

Definition at line 182 of file MethodRuleFit.h.

◆ fSepTypeS

TString TMVA::MethodRuleFit::fSepTypeS
private

Definition at line 186 of file MethodRuleFit.h.

◆ fSignalFraction

Double_t TMVA::MethodRuleFit::fSignalFraction
private

Definition at line 156 of file MethodRuleFit.h.

◆ fTreeEveFrac

Double_t TMVA::MethodRuleFit::fTreeEveFrac
private

Definition at line 181 of file MethodRuleFit.h.

◆ fUseBoost

Bool_t TMVA::MethodRuleFit::fUseBoost
private

Definition at line 191 of file MethodRuleFit.h.

◆ fUseRuleFitJF

Bool_t TMVA::MethodRuleFit::fUseRuleFitJF
private

Definition at line 175 of file MethodRuleFit.h.

Libraries for TMVA::MethodRuleFit:
[legend]

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