ROOT  6.06/09
Reference Guide
Public Member Functions | Private Member Functions | Private Attributes | Static Private Attributes | List of all members
TMVA::MethodDT Class Reference

Definition at line 61 of file MethodDT.h.

Public Member Functions

 MethodDT (const TString &jobName, const TString &methodTitle, DataSetInfo &theData, const TString &theOption="", TDirectory *theTargetDir=0)
 
 MethodDT (DataSetInfo &dsi, const TString &theWeightFile, TDirectory *theTargetDir=NULL)
 constructor from Reader More...
 
virtual ~MethodDT (void)
 destructor More...
 
virtual Bool_t HasAnalysisType (Types::EAnalysisType type, UInt_t numberClasses, UInt_t numberTargets)
 FDA can handle classification with 2 classes and regression with one regression-target. More...
 
void Train (void)
 
void AddWeightsXMLTo (void *parent) const
 
void ReadWeightsFromStream (std::istream &istr)
 
void ReadWeightsFromXML (void *wghtnode)
 
Double_t GetMvaValue (Double_t *err=0, Double_t *errUpper=0)
 returns MVA value More...
 
void DeclareOptions ()
 define the options (their key words) that can be set in the option string UseRandomisedTrees choose at each node splitting a random set of variables UseNvars use UseNvars variables in randomised trees SeparationType the separation criterion applied in the node splitting known: GiniIndex MisClassificationError CrossEntropy SDivSqrtSPlusB nEventsMin: the minimum number of events in a node (leaf criteria, stop splitting) nCuts: the number of steps in the optimisation of the cut for a node (if < 0, then step size is determined by the events) UseYesNoLeaf decide if the classification is done simply by the node type, or the S/B (from the training) in the leaf node NodePurityLimit the minimum purity to classify a node as a signal node (used in pruning and boosting to determine misclassification error rate) PruneMethod The Pruning method: known: NoPruning // switch off pruning completely ExpectedError CostComplexity PruneStrength a parameter to adjust the amount of pruning. More...
 
void ProcessOptions ()
 the option string is decoded, for available options see "DeclareOptions" More...
 
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 weightfile at hand More...
 
void GetHelpMessage () const
 
const RankingCreateRanking ()
 
Double_t PruneTree ()
 prune the decision tree if requested (good for individual trees that are best grown out, and then pruned back, while boosted decision trees are best 'small' trees to start with. More...
 
Double_t TestTreeQuality (DecisionTree *dt)
 
Double_t GetPruneStrength ()
 
void SetMinNodeSize (Double_t sizeInPercent)
 
void SetMinNodeSize (TString sizeInPercent)
 
Int_t GetNNodesBeforePruning ()
 
Int_t GetNNodes ()
 
- Public Member Functions inherited from TMVA::MethodBase
 MethodBase (const TString &jobName, Types::EMVA methodType, const TString &methodTitle, DataSetInfo &dsi, const TString &theOption="", TDirectory *theBaseDir=0)
 standard constructur More...
 
 MethodBase (Types::EMVA methodType, DataSetInfo &dsi, const TString &weightFile, TDirectory *theBaseDir=0)
 constructor used for Testing + Application of the MVA, only (no training), using given WeightFiles More...
 
virtual ~MethodBase ()
 destructor More...
 
void SetupMethod ()
 setup of methods 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...
 
virtual void CheckSetup ()
 check may be overridden by derived class (sometimes, eg, fitters are used which can only be implemented during training phase) More...
 
void AddOutput (Types::ETreeType type, Types::EAnalysisType analysisType)
 
void TrainMethod ()
 
virtual std::map< TString, Double_tOptimizeTuningParameters (TString fomType="ROCIntegral", TString fitType="FitGA")
 call the Optimzier with the set of paremeters and ranges that are meant to be tuned. More...
 
virtual void SetTuneParameters (std::map< TString, Double_t > tuneParameters)
 set the tuning parameters accoding to the argument This is just a dummy . More...
 
void SetTrainTime (Double_t trainTime)
 
Double_t GetTrainTime () const
 
void SetTestTime (Double_t testTime)
 
Double_t GetTestTime () const
 
virtual void TestClassification ()
 initialization More...
 
virtual Double_t GetKSTrainingVsTest (Char_t SorB, TString opt="X")
 
virtual void TestMulticlass ()
 test multiclass classification More...
 
virtual void TestRegression (Double_t &bias, Double_t &biasT, Double_t &dev, Double_t &devT, Double_t &rms, Double_t &rmsT, Double_t &mInf, Double_t &mInfT, Double_t &corr, Types::ETreeType type)
 calculate <sum-of-deviation-squared> of regression output versus "true" value from test sample More...
 
virtual void Reset ()
 
Double_t GetMvaValue (const TMVA::Event *const ev, Double_t *err=0, Double_t *errUpper=0)
 
const std::vector< Float_t > & GetRegressionValues (const TMVA::Event *const ev)
 
virtual const std::vector< Float_t > & GetRegressionValues ()
 
virtual const std::vector< Float_t > & GetMulticlassValues ()
 
virtual Double_t GetProba (const Event *ev)
 
virtual Double_t GetProba (Double_t mvaVal, Double_t ap_sig)
 compute likelihood ratio More...
 
virtual Double_t GetRarity (Double_t mvaVal, Types::ESBType reftype=Types::kBackground) const
 compute rarity: R(x) = Integrate_[-oo..x] { PDF(x') dx' } where PDF(x) is the PDF of the classifier's signal or background distribution More...
 
virtual void MakeClass (const TString &classFileName=TString("")) const
 create reader class for method (classification only at present) More...
 
void PrintHelpMessage () const
 prints out method-specific help method 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...
 
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...
 
virtual void WriteEvaluationHistosToFile (Types::ETreeType treetype)
 writes all MVA evaluation histograms to file More...
 
virtual void WriteMonitoringHistosToFile () const
 write special monitoring histograms to file dummy implementation here --------------— More...
 
virtual Double_t GetEfficiency (const TString &, Types::ETreeType, Double_t &err)
 fill background efficiency (resp. More...
 
virtual Double_t GetTrainingEfficiency (const TString &)
 
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 Double_t GetSignificance () const
 compute significance of mean difference significance = |<S> - |/Sqrt(RMS_S2 + RMS_B2) More...
 
virtual Double_t GetROCIntegral (TH1D *histS, TH1D *histB) const
 calculate the area (integral) under the ROC curve as a overall quality measure of the classification More...
 
virtual Double_t 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 GetMaximumSignificance (Double_t SignalEvents, Double_t BackgroundEvents, Double_t &optimal_significance_value) const
 plot significance, 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...
 
virtual Double_t GetSeparation (TH1 *, TH1 *) const
 compute "separation" defined as <s2> = (1/2) Int_-oo..+oo { (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> = (1/2) Int_-oo..+oo { (S(x) - B(x))^2/(S(x) + B(x)) dx } More...
 
virtual void GetRegressionDeviation (UInt_t tgtNum, Types::ETreeType type, Double_t &stddev, Double_t &stddev90Percent) const
 
const TStringGetJobName () const
 
const TStringGetMethodName () const
 
TString GetMethodTypeName () const
 
Types::EMVA GetMethodType () const
 
const char * GetName () const
 Returns name of object. More...
 
const TStringGetTestvarName () const
 
const TString GetProbaName () const
 
TString GetWeightFileName () const
 retrieve weight file name More...
 
void SetTestvarName (const TString &v="")
 
UInt_t GetNvar () const
 
UInt_t GetNVariables () const
 
UInt_t GetNTargets () const
 
const TStringGetInputVar (Int_t i) const
 
const TStringGetInputLabel (Int_t i) const
 
const TStringGetInputTitle (Int_t i) const
 
Double_t GetMean (Int_t ivar) const
 
Double_t GetRMS (Int_t ivar) const
 
Double_t GetXmin (Int_t ivar) const
 
Double_t GetXmax (Int_t ivar) const
 
Double_t GetSignalReferenceCut () const
 
Double_t GetSignalReferenceCutOrientation () const
 
void SetSignalReferenceCut (Double_t cut)
 
void SetSignalReferenceCutOrientation (Double_t cutOrientation)
 
TDirectoryBaseDir () const
 returns the ROOT directory where info/histograms etc of the corresponding MVA method instance are stored More...
 
TDirectoryMethodBaseDir () const
 returns the ROOT directory where all instances of the corresponding MVA method are stored More...
 
void SetMethodDir (TDirectory *methodDir)
 
void SetBaseDir (TDirectory *methodDir)
 
void SetMethodBaseDir (TDirectory *methodDir)
 
UInt_t GetTrainingTMVAVersionCode () const
 
UInt_t GetTrainingROOTVersionCode () const
 
TString GetTrainingTMVAVersionString () const
 calculates the TMVA version string from the training version code on the fly More...
 
TString GetTrainingROOTVersionString () const
 calculates the ROOT version string from the training version code on the fly More...
 
TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true)
 
const TransformationHandlerGetTransformationHandler (Bool_t takeReroutedIfAvailable=true) const
 
void RerouteTransformationHandler (TransformationHandler *fTargetTransformation)
 
DataSetData () const
 
DataSetInfoDataInfo () const
 
UInt_t GetNEvents () const
 temporary event when testing on a different DataSet than the own one 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 EventGetTrainingEvent (Long64_t ievt) const
 
const EventGetTestingEvent (Long64_t ievt) const
 
const std::vector< TMVA::Event * > & GetEventCollection (Types::ETreeType type)
 returns the event collection (i.e. More...
 
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 tbe selected as signal or background More...
 
Bool_t HasMVAPdfs () const
 
virtual void SetAnalysisType (Types::EAnalysisType type)
 
Types::EAnalysisType GetAnalysisType () const
 
Bool_t DoRegression () const
 
Bool_t DoMulticlass () const
 
void DisableWriting (Bool_t setter)
 
- Public Member Functions inherited from TMVA::IMethod
 IMethod ()
 
virtual ~IMethod ()
 
- Public Member Functions inherited from TMVA::Configurable
 Configurable (const TString &theOption="")
 
virtual ~Configurable ()
 default destructur More...
 
virtual void ParseOptions ()
 options parser More...
 
void PrintOptions () const
 prints out the options set in the options string and the defaults More...
 
const char * GetConfigName () const
 
const char * GetConfigDescription () const
 
void SetConfigName (const char *n)
 
void SetConfigDescription (const char *d)
 
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 >
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...
 
const TStringGetOptions () const
 
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...
 
void ReadOptionsFromStream (std::istream &istr)
 read option back from the weight file More...
 
void AddOptionsXMLTo (void *parent) const
 write options to XML file More...
 
void ReadOptionsFromXML (void *node)
 
void SetMsgType (EMsgType t)
 
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)
 
- Public Member Functions inherited from TObject
 TObject ()
 
 TObject (const TObject &object)
 TObject copy ctor. More...
 
TObjectoperator= (const TObject &rhs)
 TObject assignment operator. More...
 
virtual ~TObject ()
 TObject destructor. 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...
 
virtual const char * ClassName () const
 Returns name of class to which the object belongs. More...
 
virtual void Clear (Option_t *="")
 
virtual TObjectClone (const char *newname="") const
 Make a clone of an object using the Streamer facility. More...
 
virtual Int_t Compare (const TObject *obj) const
 Compare abstract method. More...
 
virtual void Copy (TObject &object) const
 Copy this to obj. More...
 
virtual void Delete (Option_t *option="")
 Delete this object. More...
 
virtual Int_t DistancetoPrimitive (Int_t px, Int_t py)
 Computes distance from point (px,py) to the object. More...
 
virtual void Draw (Option_t *option="")
 Default Draw method for all objects. More...
 
virtual void DrawClass () const
 Draw class inheritance tree of the class to which this object belongs. More...
 
virtual TObjectDrawClone (Option_t *option="") const
 Draw a clone of this object in the current pad. More...
 
virtual void Dump () const
 Dump contents of object on stdout. 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 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 UInt_t GetUniqueID () const
 Return the unique object id. More...
 
virtual const char * GetIconName () const
 Returns mime type name of object. More...
 
virtual Option_tGetOption () const
 
virtual char * GetObjectInfo (Int_t px, Int_t py) const
 Returns string containing info about the object at position (px,py). More...
 
virtual const char * GetTitle () const
 Returns title of object. More...
 
virtual Bool_t HandleTimer (TTimer *timer)
 Execute action in response of a timer timing out. More...
 
virtual ULong_t Hash () const
 Return hash value for this object. More...
 
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...
 
virtual Bool_t IsFolder () const
 Returns kTRUE in case object contains browsable objects (like containers or lists of other objects). More...
 
virtual Bool_t IsEqual (const TObject *obj) const
 Default equal comparison (objects are equal if they have the same address in memory). More...
 
virtual Bool_t IsSortable () const
 
Bool_t IsOnHeap () const
 
Bool_t IsZombie () const
 
virtual Bool_t Notify ()
 This method must be overridden to handle object notification. More...
 
virtual void ls (Option_t *option="") const
 The ls function lists the contents of a class on stdout. More...
 
virtual void Paint (Option_t *option="")
 This method must be overridden if a class wants to paint itself. More...
 
virtual void Pop ()
 Pop on object drawn in a pad to the top of the display list. More...
 
virtual void Print (Option_t *option="") const
 This method must be overridden when a class wants to print itself. More...
 
virtual Int_t Read (const char *name)
 Read contents of object with specified name from the current directory. More...
 
virtual void RecursiveRemove (TObject *obj)
 Recursively remove this object from a list. More...
 
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...
 
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 UseCurrentStyle ()
 Set current style settings in this object This function is called when either TCanvas::UseCurrentStyle or TROOT::ForceStyle have been invoked. 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...
 
voidoperator new (size_t sz)
 
voidoperator new[] (size_t sz)
 
voidoperator new (size_t sz, void *vp)
 
voidoperator new[] (size_t sz, void *vp)
 
void operator delete (void *ptr)
 Operator delete. More...
 
void operator delete[] (void *ptr)
 Operator delete []. 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)
 
void ResetBit (UInt_t f)
 
Bool_t TestBit (UInt_t f) const
 
Int_t TestBits (UInt_t f) const
 
void InvertBit (UInt_t f)
 
virtual void Info (const char *method, const char *msgfmt,...) const
 Issue info message. More...
 
virtual void Warning (const char *method, const char *msgfmt,...) const
 Issue warning message. More...
 
virtual void Error (const char *method, const char *msgfmt,...) const
 Issue error message. More...
 
virtual void SysError (const char *method, const char *msgfmt,...) const
 Issue system error message. More...
 
virtual void Fatal (const char *method, const char *msgfmt,...) const
 Issue fatal error message. 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...
 
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...
 
void Obsolete (const char *method, const char *asOfVers, const char *removedFromVers) const
 Use this method to declare a method obsolete. More...
 

Private Member Functions

void Init (void)
 common initialisation with defaults for the DT-Method More...
 

Private Attributes

std::vector< Event * > fEventSample
 
DecisionTreefTree
 
SeparationBasefSepType
 
TString fSepTypeS
 
Int_t fMinNodeEvents
 
Float_t fMinNodeSize
 
TString fMinNodeSizeS
 
Int_t fNCuts
 
Bool_t fUseYesNoLeaf
 
Double_t fNodePurityLimit
 
UInt_t fMaxDepth
 
Double_t fErrorFraction
 
Double_t fPruneStrength
 
DecisionTree::EPruneMethod fPruneMethod
 
TString fPruneMethodS
 
Bool_t fAutomatic
 
Bool_t fRandomisedTrees
 
Int_t fUseNvars
 
Bool_t fUsePoissonNvars
 
std::vector< Double_tfVariableImportance
 
Double_t fDeltaPruneStrength
 
Bool_t fPruneBeforeBoost
 

Static Private Attributes

static const Int_t fgDebugLevel = 0
 

Additional Inherited Members

- Public Types inherited from TMVA::MethodBase
enum  EWeightFileType { kROOT =0, kTEXT }
 
- Public Types inherited from TObject
enum  EStatusBits {
  kCanDelete = BIT(0), kMustCleanup = BIT(3), kObjInCanvas = BIT(3), kIsReferenced = BIT(4),
  kHasUUID = BIT(5), kCannotPick = BIT(6), kNoContextMenu = BIT(8), kInvalidObject = BIT(13)
}
 
enum  { kIsOnHeap = 0x01000000, kNotDeleted = 0x02000000, kZombie = 0x04000000, kBitMask = 0x00ffffff }
 
enum  { kSingleKey = BIT(0), kOverwrite = BIT(1), kWriteDelete = BIT(2) }
 
- Static Public Member Functions inherited from TObject
static Long_t GetDtorOnly ()
 Return destructor only flag. More...
 
static void SetDtorOnly (void *obj)
 Set destructor only flag. More...
 
static Bool_t GetObjectStat ()
 Get status of object stat flag. More...
 
static void SetObjectStat (Bool_t stat)
 Turn on/off tracking of objects in the TObjectTable. More...
 
- Public Attributes inherited from TMVA::MethodBase
const EventfTmpEvent
 
Bool_t fSetupCompleted
 
- Protected Member Functions inherited from TMVA::MethodBase
void NoErrorCalc (Double_t *const err, Double_t *const errUpper)
 
virtual void ReadWeightsFromStream (TFile &)
 
void SetWeightFileName (TString)
 set the weight file name (depreciated) More...
 
const TStringGetWeightFileDir () const
 
void SetWeightFileDir (TString fileDir)
 set directory of weight file More...
 
Bool_t IsNormalised () const
 
void SetNormalised (Bool_t norm)
 
Bool_t Verbose () const
 
Bool_t Help () const
 
const TStringGetInternalVarName (Int_t ivar) const
 
const TStringGetOriginalVarName (Int_t ivar) const
 
Bool_t HasTrainingTree () const
 
virtual void MakeClassSpecific (std::ostream &, const TString &="") const
 
virtual void MakeClassSpecificHeader (std::ostream &, const TString &="") const
 
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 IsConstructedFromWeightFile () const
 
Bool_t IgnoreEventsWithNegWeightsInTraining () const
 
- Protected Member Functions inherited from TMVA::Configurable
Bool_t LooseOptionCheckingEnabled () const
 
void EnableLooseOptions (Bool_t b=kTRUE)
 
void WriteOptionsReferenceToFile ()
 write complete options to output stream More...
 
void ResetSetFlag ()
 resets the IsSet falg for all declare options to be called before options are read from stream More...
 
const TStringGetReferenceFile () const
 
MsgLoggerLog () const
 
- Protected Member Functions inherited from TObject
void MakeZombie ()
 
virtual void DoError (int level, const char *location, const char *fmt, va_list va) const
 Interface to ErrorHandler (protected). More...
 
- Static Protected Member Functions inherited from TMVA::MethodBase
static MethodBaseGetThisBase ()
 return a pointer the base class of this method More...
 
- Protected Attributes inherited from TMVA::MethodBase
RankingfRanking
 
std::vector< TString > * fInputVars
 
Int_t fNbins
 
Int_t fNbinsMVAoutput
 
Int_t fNbinsH
 
Types::EAnalysisType fAnalysisType
 
std::vector< Float_t > * fRegressionReturnVal
 
std::vector< Float_t > * fMulticlassReturnVal
 
UInt_t fSignalClass
 
UInt_t fBackgroundClass
 

#include <TMVA/MethodDT.h>

+ Inheritance diagram for TMVA::MethodDT:
+ Collaboration diagram for TMVA::MethodDT:

Constructor & Destructor Documentation

TMVA::MethodDT::MethodDT ( const TString jobName,
const TString methodTitle,
DataSetInfo theData,
const TString theOption = "",
TDirectory theTargetDir = 0 
)
TMVA::MethodDT::MethodDT ( DataSetInfo dsi,
const TString theWeightFile,
TDirectory theTargetDir = NULL 
)

constructor from Reader

Definition at line 148 of file MethodDT.cxx.

TMVA::MethodDT::~MethodDT ( void  )
virtual

destructor

Definition at line 358 of file MethodDT.cxx.

Member Function Documentation

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

Implements TMVA::MethodBase.

Definition at line 512 of file MethodDT.cxx.

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

Implements TMVA::MethodBase.

Definition at line 555 of file MethodDT.cxx.

void TMVA::MethodDT::DeclareCompatibilityOptions ( )
virtual

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

Reimplemented from TMVA::MethodBase.

Definition at line 232 of file MethodDT.cxx.

void TMVA::MethodDT::DeclareOptions ( )
virtual

define the options (their key words) that can be set in the option string UseRandomisedTrees choose at each node splitting a random set of variables UseNvars use UseNvars variables in randomised trees SeparationType the separation criterion applied in the node splitting known: GiniIndex MisClassificationError CrossEntropy SDivSqrtSPlusB nEventsMin: the minimum number of events in a node (leaf criteria, stop splitting) nCuts: the number of steps in the optimisation of the cut for a node (if < 0, then step size is determined by the events) UseYesNoLeaf decide if the classification is done simply by the node type, or the S/B (from the training) in the leaf node NodePurityLimit the minimum purity to classify a node as a signal node (used in pruning and boosting to determine misclassification error rate) PruneMethod The Pruning method: known: NoPruning // switch off pruning completely ExpectedError CostComplexity PruneStrength a parameter to adjust the amount of pruning.

Should be large enouth such that overtraining is avoided");

Implements TMVA::MethodBase.

Definition at line 202 of file MethodDT.cxx.

void TMVA::MethodDT::GetHelpMessage ( ) const
virtual

Implements TMVA::IMethod.

Definition at line 550 of file MethodDT.cxx.

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

returns MVA value

Implements TMVA::MethodBase.

Definition at line 540 of file MethodDT.cxx.

Int_t TMVA::MethodDT::GetNNodes ( )
inline

Definition at line 111 of file MethodDT.h.

Referenced by TMVA::MethodBoost::MonitorBoost().

Int_t TMVA::MethodDT::GetNNodesBeforePruning ( )
inline

Definition at line 110 of file MethodDT.h.

Referenced by TMVA::MethodBoost::MonitorBoost().

Double_t TMVA::MethodDT::GetPruneStrength ( )
inline

Definition at line 105 of file MethodDT.h.

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

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

Implements TMVA::IMethod.

Definition at line 173 of file MethodDT.cxx.

void TMVA::MethodDT::Init ( void  )
privatevirtual

common initialisation with defaults for the DT-Method

Implements TMVA::MethodBase.

Definition at line 333 of file MethodDT.cxx.

void TMVA::MethodDT::ProcessOptions ( )
virtual

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

Implements TMVA::MethodBase.

Definition at line 244 of file MethodDT.cxx.

Double_t TMVA::MethodDT::PruneTree ( )

prune the decision tree if requested (good for individual trees that are best grown out, and then pruned back, while boosted decision trees are best 'small' trees to start with.

Well, at least the standard "optimal pruning algorithms" don't result in 'weak enough' classifiers !!

Definition at line 395 of file MethodDT.cxx.

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

Implements TMVA::MethodBase.

Definition at line 530 of file MethodDT.cxx.

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

Implements TMVA::MethodBase.

Definition at line 520 of file MethodDT.cxx.

void TMVA::MethodDT::SetMinNodeSize ( Double_t  sizeInPercent)

Definition at line 308 of file MethodDT.cxx.

void TMVA::MethodDT::SetMinNodeSize ( TString  sizeInPercent)

Definition at line 319 of file MethodDT.cxx.

Double_t TMVA::MethodDT::TestTreeQuality ( DecisionTree dt)

Definition at line 495 of file MethodDT.cxx.

void TMVA::MethodDT::Train ( void  )
virtual

Implements TMVA::MethodBase.

Definition at line 365 of file MethodDT.cxx.

Member Data Documentation

Bool_t TMVA::MethodDT::fAutomatic
private

Definition at line 140 of file MethodDT.h.

Double_t TMVA::MethodDT::fDeltaPruneStrength
private

Definition at line 146 of file MethodDT.h.

Double_t TMVA::MethodDT::fErrorFraction
private

Definition at line 136 of file MethodDT.h.

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

Definition at line 120 of file MethodDT.h.

const Int_t TMVA::MethodDT::fgDebugLevel = 0
staticprivate

Definition at line 148 of file MethodDT.h.

UInt_t TMVA::MethodDT::fMaxDepth
private

Definition at line 133 of file MethodDT.h.

Int_t TMVA::MethodDT::fMinNodeEvents
private

Definition at line 126 of file MethodDT.h.

Float_t TMVA::MethodDT::fMinNodeSize
private

Definition at line 127 of file MethodDT.h.

TString TMVA::MethodDT::fMinNodeSizeS
private

Definition at line 128 of file MethodDT.h.

Int_t TMVA::MethodDT::fNCuts
private

Definition at line 130 of file MethodDT.h.

Double_t TMVA::MethodDT::fNodePurityLimit
private

Definition at line 132 of file MethodDT.h.

Bool_t TMVA::MethodDT::fPruneBeforeBoost
private

Definition at line 151 of file MethodDT.h.

DecisionTree::EPruneMethod TMVA::MethodDT::fPruneMethod
private

Definition at line 138 of file MethodDT.h.

TString TMVA::MethodDT::fPruneMethodS
private

Definition at line 139 of file MethodDT.h.

Double_t TMVA::MethodDT::fPruneStrength
private

Definition at line 137 of file MethodDT.h.

Referenced by GetPruneStrength().

Bool_t TMVA::MethodDT::fRandomisedTrees
private

Definition at line 141 of file MethodDT.h.

SeparationBase* TMVA::MethodDT::fSepType
private

Definition at line 124 of file MethodDT.h.

TString TMVA::MethodDT::fSepTypeS
private

Definition at line 125 of file MethodDT.h.

DecisionTree* TMVA::MethodDT::fTree
private

Definition at line 122 of file MethodDT.h.

Referenced by GetNNodes(), and GetNNodesBeforePruning().

Int_t TMVA::MethodDT::fUseNvars
private

Definition at line 142 of file MethodDT.h.

Bool_t TMVA::MethodDT::fUsePoissonNvars
private

Definition at line 143 of file MethodDT.h.

Bool_t TMVA::MethodDT::fUseYesNoLeaf
private

Definition at line 131 of file MethodDT.h.

std::vector<Double_t> TMVA::MethodDT::fVariableImportance
private

Definition at line 144 of file MethodDT.h.


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