Logo ROOT  
Reference Guide
TMVA::DecisionTreeNode Class Reference

Definition at line 117 of file DecisionTreeNode.h.

Public Member Functions

 DecisionTreeNode ()
 constructor of an essentially "empty" node floating in space More...
 
 DecisionTreeNode (const DecisionTreeNode &n, DecisionTreeNode *parent=NULL)
 copy constructor of a node. More...
 
 DecisionTreeNode (Node *p, char pos)
 constructor of a daughter node as a daughter of 'p' More...
 
virtual ~DecisionTreeNode ()
 destructor More...
 
virtual void AddAttributesToNode (void *node) const
 add attribute to xml More...
 
virtual void AddContentToNode (std::stringstream &s) const
 adding attributes to tree node (well, was used in BinarySearchTree, and somehow I guess someone programmed it such that we need this in this tree too, although we don't..) More...
 
void AddToSumTarget (Float_t t)
 
void AddToSumTarget2 (Float_t t2)
 
void ClearNodeAndAllDaughters ()
 clear the nodes (their S/N, Nevents etc), just keep the structure of the tree More...
 
virtual NodeCreateNode () const
 
Double_t GetAlpha () const
 
Double_t GetAlphaMinSubtree () const
 
Double_t GetCC () const
 
Bool_t GetCutType (void) const
 return kTRUE: Cuts select signal, kFALSE: Cuts select bkg More...
 
Float_t GetCutValue (void) const
 return the cut value applied at this node More...
 
Double_t GetFisherCoeff (Int_t ivar) const
 get fisher coefficients More...
 
virtual DecisionTreeNodeGetLeft () const
 
Float_t GetNBkgEvents (void) const
 return the sum of the backgr weights in the node More...
 
Float_t GetNBkgEvents_unboosted (void) const
 return the sum of unboosted backgr weights in the node More...
 
Float_t GetNBkgEvents_unweighted (void) const
 return the sum of unweighted backgr weights in the node More...
 
Double_t GetNBValidation () const
 
Float_t GetNEvents (void) const
 return the number of events that entered the node (during training) More...
 
Float_t GetNEvents_unboosted (void) const
 return the number of unboosted events that entered the node (during training) More...
 
Float_t GetNEvents_unweighted (void) const
 return the number of unweighted events that entered the node (during training) More...
 
UInt_t GetNFisherCoeff () const
 
Double_t GetNodeR () const
 
Int_t GetNodeType (void) const
 return node type: 1 signal node, -1 bkg leave, 0 intermediate Node More...
 
Float_t GetNSigEvents (void) const
 return the sum of the signal weights in the node More...
 
Float_t GetNSigEvents_unboosted (void) const
 return the sum of unboosted signal weights in the node More...
 
Float_t GetNSigEvents_unweighted (void) const
 
Double_t GetNSValidation () const
 
Int_t GetNTerminal () const
 
virtual DecisionTreeNodeGetParent () const
 
Float_t GetPurity (void) const
 return S/(S+B) (purity) at this node (from training) More...
 
Float_t GetResponse (void) const
 return the response of the node (for regression) More...
 
virtual DecisionTreeNodeGetRight () const
 
Float_t GetRMS (void) const
 return the RMS of the response of the node (for regression) More...
 
Float_t GetSampleMax (UInt_t ivar) const
 return the maximum of variable ivar from the training sample that pass/end up in this node More...
 
Float_t GetSampleMin (UInt_t ivar) const
 return the minimum of variable ivar from the training sample that pass/end up in this node More...
 
Short_t GetSelector () const
 return index of variable used for discrimination at this node More...
 
Float_t GetSeparationGain (void) const
 return the gain in separation obtained by this nodes selection More...
 
Float_t GetSeparationIndex (void) const
 return the separation index AT this node More...
 
Double_t GetSubTreeR () const
 
Float_t GetSumTarget () const
 
Float_t GetSumTarget2 () const
 
virtual Bool_t GoesLeft (const Event &) const
 test event if it descends the tree at this node to the left More...
 
virtual Bool_t GoesRight (const Event &) const
 test event if it descends the tree at this node to the right More...
 
void IncrementNBkgEvents (Float_t b)
 increment the sum of the backgr weights in the node More...
 
void IncrementNBkgEvents_unweighted ()
 increment the sum of the backgr weights in the node More...
 
void IncrementNEvents (Float_t nev)
 
void IncrementNEvents_unweighted ()
 increment the number of events that entered the node (during training) More...
 
void IncrementNSigEvents (Float_t s)
 increment the sum of the signal weights in the node More...
 
void IncrementNSigEvents_unweighted ()
 increment the sum of the signal weights in the node More...
 
virtual TClassIsA () const
 
Bool_t IsTerminal () const
 flag indicates whether this node is terminal More...
 
virtual void Print (std::ostream &os) const
 print the node More...
 
void PrintPrune (std::ostream &os) const
 printout of the node (can be read in with ReadDataRecord) More...
 
virtual void PrintRec (std::ostream &os) const
 recursively print the node and its daughters (--> print the 'tree') More...
 
void PrintRecPrune (std::ostream &os) const
 recursive printout of the node and its daughters More...
 
virtual void ReadAttributes (void *node, UInt_t tmva_Version_Code=262657)
 
virtual void ReadContent (std::stringstream &s)
 reading attributes from tree node (well, was used in BinarySearchTree, and somehow I guess someone programmed it such that we need this in this tree too, although we don't..) More...
 
virtual Bool_t ReadDataRecord (std::istream &is, UInt_t tmva_Version_Code=262657)
 Read the data block. More...
 
void ResetValidationData ()
 temporary stored node values (number of events, etc.) that originate not from the training but from the validation data (used in pruning) More...
 
void SetAlpha (Double_t alpha)
 
void SetAlphaMinSubtree (Double_t g)
 
void SetCC (Double_t cc)
 
void SetCutType (Bool_t t)
 set true: if event variable > cutValue ==> signal , false otherwise More...
 
void SetCutValue (Float_t c)
 set the cut value applied at this node More...
 
void SetFisherCoeff (Int_t ivar, Double_t coeff)
 set fisher coefficients More...
 
virtual void SetLeft (Node *l)
 
void SetNBkgEvents (Float_t b)
 set the sum of the backgr weights in the node More...
 
void SetNBkgEvents_unboosted (Float_t b)
 set the sum of the unboosted backgr events in the node More...
 
void SetNBkgEvents_unweighted (Float_t b)
 set the sum of the unweighted backgr events in the node More...
 
void SetNBValidation (Double_t b)
 
void SetNEvents (Float_t nev)
 set the number of events that entered the node (during training) More...
 
void SetNEvents_unboosted (Float_t nev)
 set the number of unboosted events that entered the node (during training) More...
 
void SetNEvents_unweighted (Float_t nev)
 set the number of unweighted events that entered the node (during training) More...
 
void SetNFisherCoeff (Int_t nvars)
 
void SetNodeR (Double_t r)
 
void SetNodeType (Int_t t)
 set node type: 1 signal node, -1 bkg leave, 0 intermediate Node More...
 
void SetNSigEvents (Float_t s)
 set the sum of the signal weights in the node More...
 
void SetNSigEvents_unboosted (Float_t s)
 set the sum of the unboosted signal events in the node More...
 
void SetNSigEvents_unweighted (Float_t s)
 set the sum of the unweighted signal events in the node More...
 
void SetNSValidation (Double_t s)
 
void SetNTerminal (Int_t n)
 
virtual void SetParent (Node *p)
 
void SetPurity (void)
 return the S/(S+B) (purity) for the node REM: even if nodes with purity 0.01 are very PURE background nodes, they still get a small value of the purity. More...
 
void SetResponse (Float_t r)
 set the response of the node (for regression) More...
 
virtual void SetRight (Node *r)
 
void SetRMS (Float_t r)
 set the RMS of the response of the node (for regression) More...
 
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 More...
 
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 More...
 
void SetSelector (Short_t i)
 set index of variable used for discrimination at this node More...
 
void SetSeparationGain (Float_t sep)
 set the separation, or information gained BY this nodes selection More...
 
void SetSeparationIndex (Float_t sep)
 set the chosen index, measure of "purity" (separation between S and B) AT this node More...
 
void SetSubTreeR (Double_t r)
 
void SetSumTarget (Float_t t)
 
void SetSumTarget2 (Float_t t2)
 
void SetTerminal (Bool_t s=kTRUE)
 
virtual void Streamer (TBuffer &)
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 
- Public Member Functions inherited from TMVA::Node
 Node ()
 
 Node (const Node &n)
 copy constructor, make sure you don't just copy the pointer to the node, but that the parents/daughters are initialized to 0 (and set by the copy constructors of the derived classes More...
 
 Node (Node *p, char pos)
 constructor of a daughter node as a daughter of 'p' More...
 
virtual ~Node ()
 node destructor More...
 
virtual void AddAttributesToNode (void *node) const =0
 
virtual void AddContentToNode (std::stringstream &s) const =0
 
void * AddXMLTo (void *parent) const
 add attributes to XML More...
 
Int_t CountMeAndAllDaughters () const
 recursively go through the part of the tree below this node and count all daughters More...
 
virtual NodeCreateNode () const =0
 
int GetCount ()
 returns the global number of instantiated nodes More...
 
UInt_t GetDepth () const
 
virtual NodeGetLeft () const
 
virtual NodeGetParent () const
 
virtual TMVA::BinaryTreeGetParentTree () const
 
char GetPos () const
 
virtual NodeGetRight () const
 
virtual Bool_t GoesLeft (const Event &) const =0
 
virtual Bool_t GoesRight (const Event &) const =0
 
virtual TClassIsA () const
 
virtual void Print (std::ostream &os) const =0
 
virtual void PrintRec (std::ostream &os) const =0
 
virtual void ReadAttributes (void *node, UInt_t tmva_Version_Code=262657)=0
 
virtual void ReadContent (std::stringstream &s)=0
 
virtual Bool_t ReadDataRecord (std::istream &, UInt_t tmva_Version_Code=262657)=0
 
void ReadXML (void *node, UInt_t tmva_Version_Code=262657)
 read attributes from XML More...
 
void SetDepth (UInt_t d)
 
virtual void SetLeft (Node *l)
 
virtual void SetParent (Node *p)
 
virtual void SetParentTree (TMVA::BinaryTree *t)
 
void SetPos (char s)
 
virtual void SetRight (Node *r)
 
virtual void Streamer (TBuffer &)
 
void StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)
 

Static Public Member Functions

static TClassClass ()
 
static const char * Class_Name ()
 
static Version_t Class_Version ()
 
static const char * DeclFileName ()
 
static UInt_t GetTmvaVersionCode ()
 
static bool IsTraining ()
 
static void SetIsTraining (bool on)
 
static void SetTmvaVersionCode (UInt_t code)
 
- Static Public Member Functions inherited from TMVA::Node
static TClassClass ()
 
static const char * Class_Name ()
 
static Version_t Class_Version ()
 
static const char * DeclFileName ()
 

Static Protected Member Functions

static MsgLoggerLog ()
 

Protected Attributes

Bool_t fCutType
 true: if event variable > cutValue ==> signal , false otherwise More...
 
Float_t fCutValue
 cut value applied on this node to discriminate bkg against sig More...
 
std::vector< Double_tfFisherCoeff
 the fisher coeff (offset at the last element) More...
 
Bool_t fIsTerminalNode
 ! flag to set node as terminal (i.e., without deleting its descendants) More...
 
Int_t fNodeType
 Type of node: -1 == Bkg-leaf, 1 == Signal-leaf, 0 = internal. More...
 
Float_t fPurity
 the node purity More...
 
Float_t fResponse
 response value in case of regression More...
 
Float_t fRMS
 response RMS of the regression node More...
 
Short_t fSelector
 index of variable used in node selection (decision tree) More...
 
DTNodeTrainingInfofTrainInfo
 
- Protected Attributes inherited from TMVA::Node
UInt_t fDepth
 depth of the node within the tree (seen from root node) More...
 
NodefLeft
 pointers to the two "daughter" nodes More...
 
NodefParent
 the previous (parent) node More...
 
BinaryTreefParentTree
 pointer to the parent tree to which the Node belongs More...
 
char fPos
 position, i.e. it is a left (l) or right (r) daughter More...
 
NodefRight
 pointers to the two "daughter" nodes More...
 

Static Protected Attributes

static bool fgIsTraining = false
 static variable to flag training phase in which we need fTrainInfo More...
 
static UInt_t fgTmva_Version_Code = 0
 set only when read from weightfile More...
 

#include <TMVA/DecisionTreeNode.h>

Inheritance diagram for TMVA::DecisionTreeNode:
[legend]

Constructor & Destructor Documentation

◆ DecisionTreeNode() [1/3]

TMVA::DecisionTreeNode::DecisionTreeNode ( )

constructor of an essentially "empty" node floating in space

Definition at line 67 of file DecisionTreeNode.cxx.

◆ DecisionTreeNode() [2/3]

TMVA::DecisionTreeNode::DecisionTreeNode ( TMVA::Node p,
char  pos 
)

constructor of a daughter node as a daughter of 'p'

Definition at line 91 of file DecisionTreeNode.cxx.

◆ DecisionTreeNode() [3/3]

TMVA::DecisionTreeNode::DecisionTreeNode ( const DecisionTreeNode n,
DecisionTreeNode parent = NULL 
)

copy constructor of a node.

It will result in an explicit copy of the node and recursively all it's daughters

Definition at line 116 of file DecisionTreeNode.cxx.

◆ ~DecisionTreeNode()

TMVA::DecisionTreeNode::~DecisionTreeNode ( )
virtual

destructor

Definition at line 148 of file DecisionTreeNode.cxx.

Member Function Documentation

◆ AddAttributesToNode()

void TMVA::DecisionTreeNode::AddAttributesToNode ( void *  node) const
virtual

add attribute to xml

Implements TMVA::Node.

Definition at line 492 of file DecisionTreeNode.cxx.

◆ AddContentToNode()

void TMVA::DecisionTreeNode::AddContentToNode ( std::stringstream &  s) const
virtual

adding attributes to tree node (well, was used in BinarySearchTree, and somehow I guess someone programmed it such that we need this in this tree too, although we don't..)

Implements TMVA::Node.

Definition at line 526 of file DecisionTreeNode.cxx.

◆ AddToSumTarget()

void TMVA::DecisionTreeNode::AddToSumTarget ( Float_t  t)
inline

Definition at line 323 of file DecisionTreeNode.h.

◆ AddToSumTarget2()

void TMVA::DecisionTreeNode::AddToSumTarget2 ( Float_t  t2)
inline

Definition at line 324 of file DecisionTreeNode.h.

◆ Class()

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

◆ Class_Name()

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

◆ Class_Version()

static Version_t TMVA::DecisionTreeNode::Class_Version ( )
inlinestatic
Returns
Version of this class

Definition at line 381 of file DecisionTreeNode.h.

◆ ClearNodeAndAllDaughters()

void TMVA::DecisionTreeNode::ClearNodeAndAllDaughters ( )

clear the nodes (their S/N, Nevents etc), just keep the structure of the tree

Definition at line 346 of file DecisionTreeNode.cxx.

◆ CreateNode()

virtual Node * TMVA::DecisionTreeNode::CreateNode ( ) const
inlinevirtual

Implements TMVA::Node.

Definition at line 132 of file DecisionTreeNode.h.

◆ DeclFileName()

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

Definition at line 381 of file DecisionTreeNode.h.

◆ GetAlpha()

Double_t TMVA::DecisionTreeNode::GetAlpha ( ) const
inline

Definition at line 304 of file DecisionTreeNode.h.

◆ GetAlphaMinSubtree()

Double_t TMVA::DecisionTreeNode::GetAlphaMinSubtree ( ) const
inline

Definition at line 308 of file DecisionTreeNode.h.

◆ GetCC()

Double_t TMVA::DecisionTreeNode::GetCC ( ) const
inline

Definition at line 340 of file DecisionTreeNode.h.

◆ GetCutType()

Bool_t TMVA::DecisionTreeNode::GetCutType ( void  ) const
inline

return kTRUE: Cuts select signal, kFALSE: Cuts select bkg

Definition at line 160 of file DecisionTreeNode.h.

◆ GetCutValue()

Float_t TMVA::DecisionTreeNode::GetCutValue ( void  ) const
inline

return the cut value applied at this node

Definition at line 155 of file DecisionTreeNode.h.

◆ GetFisherCoeff()

Double_t TMVA::DecisionTreeNode::GetFisherCoeff ( Int_t  ivar) const
inline

get fisher coefficients

Definition at line 139 of file DecisionTreeNode.h.

◆ GetLeft()

virtual DecisionTreeNode * TMVA::DecisionTreeNode::GetLeft ( ) const
inlinevirtual

Reimplemented from TMVA::Node.

Definition at line 283 of file DecisionTreeNode.h.

◆ GetNBkgEvents()

Float_t TMVA::DecisionTreeNode::GetNBkgEvents ( void  ) const
inline

return the sum of the backgr weights in the node

Definition at line 233 of file DecisionTreeNode.h.

◆ GetNBkgEvents_unboosted()

Float_t TMVA::DecisionTreeNode::GetNBkgEvents_unboosted ( void  ) const
inline

return the sum of unboosted backgr weights in the node

Definition at line 251 of file DecisionTreeNode.h.

◆ GetNBkgEvents_unweighted()

Float_t TMVA::DecisionTreeNode::GetNBkgEvents_unweighted ( void  ) const
inline

return the sum of unweighted backgr weights in the node

Definition at line 242 of file DecisionTreeNode.h.

◆ GetNBValidation()

Double_t TMVA::DecisionTreeNode::GetNBValidation ( ) const
inline

Definition at line 317 of file DecisionTreeNode.h.

◆ GetNEvents()

Float_t TMVA::DecisionTreeNode::GetNEvents ( void  ) const
inline

return the number of events that entered the node (during training)

Definition at line 236 of file DecisionTreeNode.h.

◆ GetNEvents_unboosted()

Float_t TMVA::DecisionTreeNode::GetNEvents_unboosted ( void  ) const
inline

return the number of unboosted events that entered the node (during training)

Definition at line 254 of file DecisionTreeNode.h.

◆ GetNEvents_unweighted()

Float_t TMVA::DecisionTreeNode::GetNEvents_unweighted ( void  ) const
inline

return the number of unweighted events that entered the node (during training)

Definition at line 245 of file DecisionTreeNode.h.

◆ GetNFisherCoeff()

UInt_t TMVA::DecisionTreeNode::GetNFisherCoeff ( ) const
inline

Definition at line 135 of file DecisionTreeNode.h.

◆ GetNodeR()

Double_t TMVA::DecisionTreeNode::GetNodeR ( ) const
inline

Definition at line 294 of file DecisionTreeNode.h.

◆ GetNodeType()

Int_t TMVA::DecisionTreeNode::GetNodeType ( void  ) const
inline

return node type: 1 signal node, -1 bkg leave, 0 intermediate Node

Definition at line 165 of file DecisionTreeNode.h.

◆ GetNSigEvents()

Float_t TMVA::DecisionTreeNode::GetNSigEvents ( void  ) const
inline

return the sum of the signal weights in the node

Definition at line 230 of file DecisionTreeNode.h.

◆ GetNSigEvents_unboosted()

Float_t TMVA::DecisionTreeNode::GetNSigEvents_unboosted ( void  ) const
inline

return the sum of unboosted signal weights in the node

Definition at line 248 of file DecisionTreeNode.h.

◆ GetNSigEvents_unweighted()

Float_t TMVA::DecisionTreeNode::GetNSigEvents_unweighted ( void  ) const
inline

Definition at line 239 of file DecisionTreeNode.h.

◆ GetNSValidation()

Double_t TMVA::DecisionTreeNode::GetNSValidation ( ) const
inline

Definition at line 318 of file DecisionTreeNode.h.

◆ GetNTerminal()

Int_t TMVA::DecisionTreeNode::GetNTerminal ( ) const
inline

Definition at line 312 of file DecisionTreeNode.h.

◆ GetParent()

virtual DecisionTreeNode * TMVA::DecisionTreeNode::GetParent ( ) const
inlinevirtual

Reimplemented from TMVA::Node.

Definition at line 285 of file DecisionTreeNode.h.

◆ GetPurity()

Float_t TMVA::DecisionTreeNode::GetPurity ( void  ) const
inline

return S/(S+B) (purity) at this node (from training)

Definition at line 168 of file DecisionTreeNode.h.

◆ GetResponse()

Float_t TMVA::DecisionTreeNode::GetResponse ( void  ) const
inline

return the response of the node (for regression)

Definition at line 176 of file DecisionTreeNode.h.

◆ GetRight()

virtual DecisionTreeNode * TMVA::DecisionTreeNode::GetRight ( ) const
inlinevirtual

Reimplemented from TMVA::Node.

Definition at line 284 of file DecisionTreeNode.h.

◆ GetRMS()

Float_t TMVA::DecisionTreeNode::GetRMS ( void  ) const
inline

return the RMS of the response of the node (for regression)

Definition at line 182 of file DecisionTreeNode.h.

◆ GetSampleMax()

Float_t TMVA::DecisionTreeNode::GetSampleMax ( UInt_t  ivar) const

return the maximum of variable ivar from the training sample that pass/end up in this node

Definition at line 424 of file DecisionTreeNode.cxx.

◆ GetSampleMin()

Float_t TMVA::DecisionTreeNode::GetSampleMin ( UInt_t  ivar) const

return the minimum of variable ivar from the training sample that pass/end up in this node

Definition at line 413 of file DecisionTreeNode.cxx.

◆ GetSelector()

Short_t TMVA::DecisionTreeNode::GetSelector ( ) const
inline

return index of variable used for discrimination at this node

Definition at line 150 of file DecisionTreeNode.h.

◆ GetSeparationGain()

Float_t TMVA::DecisionTreeNode::GetSeparationGain ( void  ) const
inline

return the gain in separation obtained by this nodes selection

Definition at line 266 of file DecisionTreeNode.h.

◆ GetSeparationIndex()

Float_t TMVA::DecisionTreeNode::GetSeparationIndex ( void  ) const
inline

return the separation index AT this node

Definition at line 260 of file DecisionTreeNode.h.

◆ GetSubTreeR()

Double_t TMVA::DecisionTreeNode::GetSubTreeR ( ) const
inline

Definition at line 298 of file DecisionTreeNode.h.

◆ GetSumTarget()

Float_t TMVA::DecisionTreeNode::GetSumTarget ( ) const
inline

Definition at line 326 of file DecisionTreeNode.h.

◆ GetSumTarget2()

Float_t TMVA::DecisionTreeNode::GetSumTarget2 ( ) const
inline

Definition at line 327 of file DecisionTreeNode.h.

◆ GetTmvaVersionCode()

UInt_t TMVA::DecisionTreeNode::GetTmvaVersionCode ( )
static

Definition at line 558 of file DecisionTreeNode.cxx.

◆ GoesLeft()

Bool_t TMVA::DecisionTreeNode::GoesLeft ( const Event e) const
virtual

test event if it descends the tree at this node to the left

Implements TMVA::Node.

Definition at line 179 of file DecisionTreeNode.cxx.

◆ GoesRight()

Bool_t TMVA::DecisionTreeNode::GoesRight ( const Event e) const
virtual

test event if it descends the tree at this node to the right

Implements TMVA::Node.

Definition at line 155 of file DecisionTreeNode.cxx.

◆ IncrementNBkgEvents()

void TMVA::DecisionTreeNode::IncrementNBkgEvents ( Float_t  b)
inline

increment the sum of the backgr weights in the node

Definition at line 215 of file DecisionTreeNode.h.

◆ IncrementNBkgEvents_unweighted()

void TMVA::DecisionTreeNode::IncrementNBkgEvents_unweighted ( )
inline

increment the sum of the backgr weights in the node

Definition at line 224 of file DecisionTreeNode.h.

◆ IncrementNEvents()

void TMVA::DecisionTreeNode::IncrementNEvents ( Float_t  nev)
inline

Definition at line 218 of file DecisionTreeNode.h.

◆ IncrementNEvents_unweighted()

void TMVA::DecisionTreeNode::IncrementNEvents_unweighted ( )
inline

increment the number of events that entered the node (during training)

Definition at line 227 of file DecisionTreeNode.h.

◆ IncrementNSigEvents()

void TMVA::DecisionTreeNode::IncrementNSigEvents ( Float_t  s)
inline

increment the sum of the signal weights in the node

Definition at line 212 of file DecisionTreeNode.h.

◆ IncrementNSigEvents_unweighted()

void TMVA::DecisionTreeNode::IncrementNSigEvents_unweighted ( )
inline

increment the sum of the signal weights in the node

Definition at line 221 of file DecisionTreeNode.h.

◆ IsA()

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

Reimplemented from TMVA::Node.

Definition at line 381 of file DecisionTreeNode.h.

◆ IsTerminal()

Bool_t TMVA::DecisionTreeNode::IsTerminal ( ) const
inline

flag indicates whether this node is terminal

Definition at line 334 of file DecisionTreeNode.h.

◆ IsTraining()

Bool_t TMVA::DecisionTreeNode::IsTraining ( )
static

Definition at line 554 of file DecisionTreeNode.cxx.

◆ Log()

TMVA::MsgLogger & TMVA::DecisionTreeNode::Log ( )
staticprotected

Definition at line 540 of file DecisionTreeNode.cxx.

◆ Print()

void TMVA::DecisionTreeNode::Print ( std::ostream &  os) const
virtual

print the node

Implements TMVA::Node.

Definition at line 209 of file DecisionTreeNode.cxx.

◆ PrintPrune()

void TMVA::DecisionTreeNode::PrintPrune ( std::ostream &  os) const

printout of the node (can be read in with ReadDataRecord)

Definition at line 381 of file DecisionTreeNode.cxx.

◆ PrintRec()

void TMVA::DecisionTreeNode::PrintRec ( std::ostream &  os) const
virtual

recursively print the node and its daughters (--> print the 'tree')

Implements TMVA::Node.

Definition at line 241 of file DecisionTreeNode.cxx.

◆ PrintRecPrune()

void TMVA::DecisionTreeNode::PrintRecPrune ( std::ostream &  os) const

recursive printout of the node and its daughters

Definition at line 393 of file DecisionTreeNode.cxx.

◆ ReadAttributes()

void TMVA::DecisionTreeNode::ReadAttributes ( void *  node,
UInt_t  tmva_Version_Code = 262657 
)
virtual

Implements TMVA::Node.

Definition at line 455 of file DecisionTreeNode.cxx.

◆ ReadContent()

void TMVA::DecisionTreeNode::ReadContent ( std::stringstream &  s)
virtual

reading attributes from tree node (well, was used in BinarySearchTree, and somehow I guess someone programmed it such that we need this in this tree too, although we don't..)

Implements TMVA::Node.

Definition at line 535 of file DecisionTreeNode.cxx.

◆ ReadDataRecord()

Bool_t TMVA::DecisionTreeNode::ReadDataRecord ( std::istream &  is,
UInt_t  tmva_Version_Code = 262657 
)
virtual

Read the data block.

Implements TMVA::Node.

Definition at line 272 of file DecisionTreeNode.cxx.

◆ ResetValidationData()

void TMVA::DecisionTreeNode::ResetValidationData ( )

temporary stored node values (number of events, etc.) that originate not from the training but from the validation data (used in pruning)

Definition at line 366 of file DecisionTreeNode.cxx.

◆ SetAlpha()

void TMVA::DecisionTreeNode::SetAlpha ( Double_t  alpha)
inline

Definition at line 303 of file DecisionTreeNode.h.

◆ SetAlphaMinSubtree()

void TMVA::DecisionTreeNode::SetAlphaMinSubtree ( Double_t  g)
inline

Definition at line 307 of file DecisionTreeNode.h.

◆ SetCC()

void TMVA::DecisionTreeNode::SetCC ( Double_t  cc)

Definition at line 403 of file DecisionTreeNode.cxx.

◆ SetCutType()

void TMVA::DecisionTreeNode::SetCutType ( Bool_t  t)
inline

set true: if event variable > cutValue ==> signal , false otherwise

Definition at line 158 of file DecisionTreeNode.h.

◆ SetCutValue()

void TMVA::DecisionTreeNode::SetCutValue ( Float_t  c)
inline

set the cut value applied at this node

Definition at line 153 of file DecisionTreeNode.h.

◆ SetFisherCoeff()

void TMVA::DecisionTreeNode::SetFisherCoeff ( Int_t  ivar,
Double_t  coeff 
)

set fisher coefficients

Definition at line 515 of file DecisionTreeNode.cxx.

◆ SetIsTraining()

void TMVA::DecisionTreeNode::SetIsTraining ( bool  on)
static

Definition at line 546 of file DecisionTreeNode.cxx.

◆ SetLeft()

virtual void TMVA::DecisionTreeNode::SetLeft ( Node l)
inlinevirtual

Reimplemented from TMVA::Node.

Definition at line 288 of file DecisionTreeNode.h.

◆ SetNBkgEvents()

void TMVA::DecisionTreeNode::SetNBkgEvents ( Float_t  b)
inline

set the sum of the backgr weights in the node

Definition at line 188 of file DecisionTreeNode.h.

◆ SetNBkgEvents_unboosted()

void TMVA::DecisionTreeNode::SetNBkgEvents_unboosted ( Float_t  b)
inline

set the sum of the unboosted backgr events in the node

Definition at line 206 of file DecisionTreeNode.h.

◆ SetNBkgEvents_unweighted()

void TMVA::DecisionTreeNode::SetNBkgEvents_unweighted ( Float_t  b)
inline

set the sum of the unweighted backgr events in the node

Definition at line 197 of file DecisionTreeNode.h.

◆ SetNBValidation()

void TMVA::DecisionTreeNode::SetNBValidation ( Double_t  b)
inline

Definition at line 315 of file DecisionTreeNode.h.

◆ SetNEvents()

void TMVA::DecisionTreeNode::SetNEvents ( Float_t  nev)
inline

set the number of events that entered the node (during training)

Definition at line 191 of file DecisionTreeNode.h.

◆ SetNEvents_unboosted()

void TMVA::DecisionTreeNode::SetNEvents_unboosted ( Float_t  nev)
inline

set the number of unboosted events that entered the node (during training)

Definition at line 209 of file DecisionTreeNode.h.

◆ SetNEvents_unweighted()

void TMVA::DecisionTreeNode::SetNEvents_unweighted ( Float_t  nev)
inline

set the number of unweighted events that entered the node (during training)

Definition at line 200 of file DecisionTreeNode.h.

◆ SetNFisherCoeff()

void TMVA::DecisionTreeNode::SetNFisherCoeff ( Int_t  nvars)
inline

Definition at line 134 of file DecisionTreeNode.h.

◆ SetNodeR()

void TMVA::DecisionTreeNode::SetNodeR ( Double_t  r)
inline

Definition at line 293 of file DecisionTreeNode.h.

◆ SetNodeType()

void TMVA::DecisionTreeNode::SetNodeType ( Int_t  t)
inline

set node type: 1 signal node, -1 bkg leave, 0 intermediate Node

Definition at line 163 of file DecisionTreeNode.h.

◆ SetNSigEvents()

void TMVA::DecisionTreeNode::SetNSigEvents ( Float_t  s)
inline

set the sum of the signal weights in the node

Definition at line 185 of file DecisionTreeNode.h.

◆ SetNSigEvents_unboosted()

void TMVA::DecisionTreeNode::SetNSigEvents_unboosted ( Float_t  s)
inline

set the sum of the unboosted signal events in the node

Definition at line 203 of file DecisionTreeNode.h.

◆ SetNSigEvents_unweighted()

void TMVA::DecisionTreeNode::SetNSigEvents_unweighted ( Float_t  s)
inline

set the sum of the unweighted signal events in the node

Definition at line 194 of file DecisionTreeNode.h.

◆ SetNSValidation()

void TMVA::DecisionTreeNode::SetNSValidation ( Double_t  s)
inline

Definition at line 316 of file DecisionTreeNode.h.

◆ SetNTerminal()

void TMVA::DecisionTreeNode::SetNTerminal ( Int_t  n)
inline

Definition at line 311 of file DecisionTreeNode.h.

◆ SetParent()

virtual void TMVA::DecisionTreeNode::SetParent ( Node p)
inlinevirtual

Reimplemented from TMVA::Node.

Definition at line 290 of file DecisionTreeNode.h.

◆ SetPurity()

void TMVA::DecisionTreeNode::SetPurity ( void  )

return the S/(S+B) (purity) for the node REM: even if nodes with purity 0.01 are very PURE background nodes, they still get a small value of the purity.

Definition at line 191 of file DecisionTreeNode.cxx.

◆ SetResponse()

void TMVA::DecisionTreeNode::SetResponse ( Float_t  r)
inline

set the response of the node (for regression)

Definition at line 173 of file DecisionTreeNode.h.

◆ SetRight()

virtual void TMVA::DecisionTreeNode::SetRight ( Node r)
inlinevirtual

Reimplemented from TMVA::Node.

Definition at line 289 of file DecisionTreeNode.h.

◆ SetRMS()

void TMVA::DecisionTreeNode::SetRMS ( Float_t  r)
inline

set the RMS of the response of the node (for regression)

Definition at line 179 of file DecisionTreeNode.h.

◆ SetSampleMax()

void TMVA::DecisionTreeNode::SetSampleMax ( UInt_t  ivar,
Float_t  xmax 
)

set the maximum of variable ivar from the training sample that pass/end up in this node

Definition at line 446 of file DecisionTreeNode.cxx.

◆ SetSampleMin()

void TMVA::DecisionTreeNode::SetSampleMin ( UInt_t  ivar,
Float_t  xmin 
)

set the minimum of variable ivar from the training sample that pass/end up in this node

Definition at line 435 of file DecisionTreeNode.cxx.

◆ SetSelector()

void TMVA::DecisionTreeNode::SetSelector ( Short_t  i)
inline

set index of variable used for discrimination at this node

Definition at line 148 of file DecisionTreeNode.h.

◆ SetSeparationGain()

void TMVA::DecisionTreeNode::SetSeparationGain ( Float_t  sep)
inline

set the separation, or information gained BY this nodes selection

Definition at line 263 of file DecisionTreeNode.h.

◆ SetSeparationIndex()

void TMVA::DecisionTreeNode::SetSeparationIndex ( Float_t  sep)
inline

set the chosen index, measure of "purity" (separation between S and B) AT this node

Definition at line 257 of file DecisionTreeNode.h.

◆ SetSubTreeR()

void TMVA::DecisionTreeNode::SetSubTreeR ( Double_t  r)
inline

Definition at line 297 of file DecisionTreeNode.h.

◆ SetSumTarget()

void TMVA::DecisionTreeNode::SetSumTarget ( Float_t  t)
inline

Definition at line 320 of file DecisionTreeNode.h.

◆ SetSumTarget2()

void TMVA::DecisionTreeNode::SetSumTarget2 ( Float_t  t2)
inline

Definition at line 321 of file DecisionTreeNode.h.

◆ SetTerminal()

void TMVA::DecisionTreeNode::SetTerminal ( Bool_t  s = kTRUE)
inline

Definition at line 335 of file DecisionTreeNode.h.

◆ SetTmvaVersionCode()

void TMVA::DecisionTreeNode::SetTmvaVersionCode ( UInt_t  code)
static

Definition at line 550 of file DecisionTreeNode.cxx.

◆ Streamer()

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

Reimplemented from TMVA::Node.

◆ StreamerNVirtual()

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

Definition at line 381 of file DecisionTreeNode.h.

Member Data Documentation

◆ fCutType

Bool_t TMVA::DecisionTreeNode::fCutType
protected

true: if event variable > cutValue ==> signal , false otherwise

Definition at line 367 of file DecisionTreeNode.h.

◆ fCutValue

Float_t TMVA::DecisionTreeNode::fCutValue
protected

cut value applied on this node to discriminate bkg against sig

Definition at line 366 of file DecisionTreeNode.h.

◆ fFisherCoeff

std::vector<Double_t> TMVA::DecisionTreeNode::fFisherCoeff
protected

the fisher coeff (offset at the last element)

Definition at line 364 of file DecisionTreeNode.h.

◆ fgIsTraining

Bool_t TMVA::DecisionTreeNode::fgIsTraining = false
staticprotected

static variable to flag training phase in which we need fTrainInfo

Definition at line 361 of file DecisionTreeNode.h.

◆ fgTmva_Version_Code

UInt_t TMVA::DecisionTreeNode::fgTmva_Version_Code = 0
staticprotected

set only when read from weightfile

Definition at line 362 of file DecisionTreeNode.h.

◆ fIsTerminalNode

Bool_t TMVA::DecisionTreeNode::fIsTerminalNode
protected

! flag to set node as terminal (i.e., without deleting its descendants)

Definition at line 375 of file DecisionTreeNode.h.

◆ fNodeType

Int_t TMVA::DecisionTreeNode::fNodeType
protected

Type of node: -1 == Bkg-leaf, 1 == Signal-leaf, 0 = internal.

Definition at line 372 of file DecisionTreeNode.h.

◆ fPurity

Float_t TMVA::DecisionTreeNode::fPurity
protected

the node purity

Definition at line 373 of file DecisionTreeNode.h.

◆ fResponse

Float_t TMVA::DecisionTreeNode::fResponse
protected

response value in case of regression

Definition at line 370 of file DecisionTreeNode.h.

◆ fRMS

Float_t TMVA::DecisionTreeNode::fRMS
protected

response RMS of the regression node

Definition at line 371 of file DecisionTreeNode.h.

◆ fSelector

Short_t TMVA::DecisionTreeNode::fSelector
protected

index of variable used in node selection (decision tree)

Definition at line 368 of file DecisionTreeNode.h.

◆ fTrainInfo

DTNodeTrainingInfo* TMVA::DecisionTreeNode::fTrainInfo
mutableprotected

Definition at line 377 of file DecisionTreeNode.h.

Libraries for TMVA::DecisionTreeNode:
[legend]

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