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30 #ifndef ROOT_TMVA_DecisionTreeNode
31 #define ROOT_TMVA_DecisionTreeNode
268 virtual void Print( std::ostream& os )
const;
271 virtual void PrintRec( std::ostream& os )
const;
virtual void PrintRec(std::ostream &os) const
recursively print the node and its daughters (--> print the 'tree')
virtual Bool_t ReadDataRecord(std::istream &is, UInt_t tmva_Version_Code=TMVA_VERSION_CODE)
Read the data block.
void SetSeparationIndex(Float_t sep)
Float_t GetNEvents_unboosted(void) const
Double_t GetAlpha() const
void IncrementNBkgEvents_unweighted()
virtual Node * CreateNode() const
Float_t GetSampleMax(UInt_t ivar) const
return the maximum of variable ivar from the training sample that pass/end up in this node
static void SetIsTraining(bool on)
void SetNSigEvents_unweighted(Float_t s)
void SetNTerminal(Int_t n)
void AddToSumTarget(Float_t t)
void SetNBkgEvents_unboosted(Float_t b)
void IncrementNEvents(Float_t nev)
Int_t GetNodeType(void) const
void SetSeparationGain(Float_t sep)
void SetNBkgEvents_unweighted(Float_t b)
Double_t GetNodeR() const
void PrintPrune(std::ostream &os) const
printout of the node (can be read in with ReadDataRecord)
Float_t GetRMS(void) const
Double_t GetSubTreeR() const
static UInt_t fgTmva_Version_Code
void ClearNodeAndAllDaughters()
clear the nodes (their S/N, Nevents etc), just keep the structure of the tree
Float_t GetSeparationGain(void) const
static constexpr double s
void SetResponse(Float_t r)
virtual Bool_t GoesRight(const Event &) const
test event if it descends the tree at this node to the right
void SetCutType(Bool_t t)
void SetNSigEvents(Float_t s)
Double_t GetNSValidation() const
void SetSampleMax(UInt_t ivar, Float_t xmax)
set the maximum of variable ivar from the training sample that pass/end up in this node
Float_t fNSigEvents_unweighted
std::vector< Float_t > fSampleMin
virtual void SetParent(Node *p)
Float_t fNEvents_unboosted
Bool_t IsTerminal() const
void SetCutValue(Float_t c)
Double_t GetFisherCoeff(Int_t ivar) const
Node for the BinarySearch or Decision Trees.
Float_t GetNBkgEvents_unboosted(void) const
void SetNEvents_unboosted(Float_t nev)
Float_t fNSigEvents_unboosted
Float_t GetNSigEvents(void) const
Double_t GetNBValidation() const
void SetFisherCoeff(Int_t ivar, Double_t coeff)
set fisher coefficients
Float_t GetSumTarget2() const
void SetNodeR(Double_t r)
Float_t GetNBkgEvents_unweighted(void) const
void SetNEvents_unweighted(Float_t nev)
virtual ~DecisionTreeNode()
destructor
void SetSampleMin(UInt_t ivar, Float_t xmin)
set the minimum of variable ivar from the training sample that pass/end up in this node
virtual DecisionTreeNode * GetLeft() const
void IncrementNSigEvents(Float_t s)
void SetSumTarget2(Float_t t2)
Float_t GetNBkgEvents(void) const
void PrintRecPrune(std::ostream &os) const
recursive printout of the node and its daughters
void SetNBValidation(Double_t b)
void SetPurity(void)
return the S/(S+B) (purity) for the node REM: even if nodes with purity 0.01 are very PURE background...
Short_t GetSelector() const
void SetNEvents(Float_t nev)
Float_t GetPurity(void) const
static UInt_t GetTmvaVersionCode()
void SetSubTreeR(Double_t r)
virtual Bool_t GoesLeft(const Event &) const
test event if it descends the tree at this node to the left
Bool_t GetCutType(void) const
Float_t fNBkgEvents_unweighted
virtual void SetLeft(Node *l)
virtual void ReadAttributes(void *node, UInt_t tmva_Version_Code=TMVA_VERSION_CODE)
virtual void AddAttributesToNode(void *node) const
add attribute to xml
virtual void AddContentToNode(std::stringstream &s) const
adding attributes to tree node (well, was used in BinarySearchTree, and somehow I guess someone progr...
Float_t GetSumTarget() const
Float_t GetNSigEvents_unweighted(void) const
Float_t GetCutValue(void) const
void AddToSumTarget2(Float_t t2)
void SetNSigEvents_unboosted(Float_t s)
void SetNodeType(Int_t t)
ostringstream derivative to redirect and format output
static void SetTmvaVersionCode(UInt_t code)
Float_t fNEvents_unweighted
#define TMVA_VERSION_CODE
DTNodeTrainingInfo(const DTNodeTrainingInfo &n)
Double_t GetAlphaMinSubtree() const
UInt_t GetNFisherCoeff() const
DecisionTreeNode()
constructor of an essentially "empty" node floating in space
#define ClassDef(name, id)
void SetNSValidation(Double_t s)
std::vector< Float_t > fSampleMax
Float_t GetNEvents_unweighted(void) const
void IncrementNEvents_unweighted()
void ResetValidationData()
temporary stored node values (number of events, etc.) that originate not from the training but from t...
void SetNFisherCoeff(Int_t nvars)
Int_t GetNTerminal() const
void SetAlpha(Double_t alpha)
std::vector< Double_t > fFisherCoeff
void SetTerminal(Bool_t s=kTRUE)
Float_t GetResponse(void) const
void IncrementNBkgEvents(Float_t b)
void SetSelector(Short_t i)
virtual DecisionTreeNode * GetRight() const
Float_t fNBkgEvents_unboosted
virtual void ReadContent(std::stringstream &s)
reading attributes from tree node (well, was used in BinarySearchTree, and somehow I guess someone pr...
virtual void SetRight(Node *r)
void SetNBkgEvents(Float_t b)
void IncrementNSigEvents_unweighted()
Float_t GetSampleMin(UInt_t ivar) const
return the minimum of variable ivar from the training sample that pass/end up in this node
Float_t GetNSigEvents_unboosted(void) const
void SetSumTarget(Float_t t)
virtual DecisionTreeNode * GetParent() const
create variable transformations
Float_t GetSeparationIndex(void) const
Float_t GetNEvents(void) const
DTNodeTrainingInfo * fTrainInfo
flag to set node as terminal (i.e., without deleting its descendants)
virtual void Print(std::ostream &os) const
print the node
void SetAlphaMinSubtree(Double_t g)