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ROOT 6.10/09 Reference Guide |
Definition at line 116 of file DecisionTreeNode.h.
Public Member Functions | |
DecisionTreeNode () | |
constructor of an essentially "empty" node floating in space More... | |
DecisionTreeNode (Node *p, char pos) | |
constructor of a daughter node as a daughter of 'p' More... | |
DecisionTreeNode (const DecisionTreeNode &n, DecisionTreeNode *parent=NULL) | |
copy constructor of a node. 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 Node * | CreateNode () const |
Double_t | GetAlpha () const |
Double_t | GetAlphaMinSubtree () const |
Double_t | GetCC () const |
Bool_t | GetCutType (void) const |
Float_t | GetCutValue (void) const |
Double_t | GetFisherCoeff (Int_t ivar) const |
virtual DecisionTreeNode * | GetLeft () const |
Float_t | GetNBkgEvents (void) const |
Float_t | GetNBkgEvents_unboosted (void) const |
Float_t | GetNBkgEvents_unweighted (void) const |
Double_t | GetNBValidation () const |
Float_t | GetNEvents (void) const |
Float_t | GetNEvents_unboosted (void) const |
Float_t | GetNEvents_unweighted (void) const |
UInt_t | GetNFisherCoeff () const |
Double_t | GetNodeR () const |
Int_t | GetNodeType (void) const |
Float_t | GetNSigEvents (void) const |
Float_t | GetNSigEvents_unboosted (void) const |
Float_t | GetNSigEvents_unweighted (void) const |
Double_t | GetNSValidation () const |
Int_t | GetNTerminal () const |
virtual DecisionTreeNode * | GetParent () const |
Float_t | GetPurity (void) const |
Float_t | GetResponse (void) const |
virtual DecisionTreeNode * | GetRight () const |
Float_t | GetRMS (void) 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 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 |
Float_t | GetSeparationGain (void) const |
Float_t | GetSeparationIndex (void) const |
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) |
void | IncrementNBkgEvents_unweighted () |
void | IncrementNEvents (Float_t nev) |
void | IncrementNEvents_unweighted () |
void | IncrementNSigEvents (Float_t s) |
void | IncrementNSigEvents_unweighted () |
Bool_t | IsTerminal () const |
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=TMVA_VERSION_CODE) |
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=TMVA_VERSION_CODE) |
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) |
void | SetCutValue (Float_t c) |
void | SetFisherCoeff (Int_t ivar, Double_t coeff) |
set fisher coefficients More... | |
virtual void | SetLeft (Node *l) |
void | SetNBkgEvents (Float_t b) |
void | SetNBkgEvents_unboosted (Float_t b) |
void | SetNBkgEvents_unweighted (Float_t b) |
void | SetNBValidation (Double_t b) |
void | SetNEvents (Float_t nev) |
void | SetNEvents_unboosted (Float_t nev) |
void | SetNEvents_unweighted (Float_t nev) |
void | SetNFisherCoeff (Int_t nvars) |
void | SetNodeR (Double_t r) |
void | SetNodeType (Int_t t) |
void | SetNSigEvents (Float_t s) |
void | SetNSigEvents_unboosted (Float_t s) |
void | SetNSigEvents_unweighted (Float_t s) |
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) |
virtual void | SetRight (Node *r) |
void | SetRMS (Float_t r) |
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) |
void | SetSeparationGain (Float_t sep) |
void | SetSeparationIndex (Float_t sep) |
void | SetSubTreeR (Double_t r) |
void | SetSumTarget (Float_t t) |
void | SetSumTarget2 (Float_t t2) |
void | SetTerminal (Bool_t s=kTRUE) |
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Node () | |
Node (Node *p, char pos) | |
constructor of a daughter node as a daughter of 'p' More... | |
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... | |
virtual | ~Node () |
node destructor More... | |
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... | |
int | GetCount () |
returns the global number of instantiated nodes More... | |
UInt_t | GetDepth () const |
virtual TMVA::BinaryTree * | GetParentTree () const |
char | GetPos () const |
void | ReadXML (void *node, UInt_t tmva_Version_Code=TMVA_VERSION_CODE) |
read attributes from XML More... | |
void | SetDepth (UInt_t d) |
virtual void | SetParentTree (TMVA::BinaryTree *t) |
void | SetPos (char s) |
Static Public Attributes | |
static bool | fgIsTraining = false |
static UInt_t | fgTmva_Version_Code = 0 |
Static Protected Member Functions | |
static MsgLogger & | Log () |
Protected Attributes | |
Bool_t | fCutType |
Float_t | fCutValue |
std::vector< Double_t > | fFisherCoeff |
Bool_t | fIsTerminalNode |
Int_t | fNodeType |
Float_t | fPurity |
Float_t | fResponse |
Float_t | fRMS |
Short_t | fSelector |
DTNodeTrainingInfo * | fTrainInfo |
flag to set node as terminal (i.e., without deleting its descendants) More... | |
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UInt_t | fDepth |
Node * | fLeft |
Node * | fParent |
BinaryTree * | fParentTree |
char | fPos |
Node * | fRight |
#include <TMVA/DecisionTreeNode.h>
TMVA::DecisionTreeNode::DecisionTreeNode | ( | ) |
constructor of an essentially "empty" node floating in space
Definition at line 67 of file DecisionTreeNode.cxx.
TMVA::DecisionTreeNode::DecisionTreeNode | ( | TMVA::Node * | p, |
char | pos | ||
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constructor of a daughter node as a daughter of 'p'
Definition at line 91 of file DecisionTreeNode.cxx.
TMVA::DecisionTreeNode::DecisionTreeNode | ( | const DecisionTreeNode & | n, |
DecisionTreeNode * | parent = NULL |
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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.
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destructor
Definition at line 148 of file DecisionTreeNode.cxx.
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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.
Definition at line 325 of file DecisionTreeNode.h.
Definition at line 326 of file DecisionTreeNode.h.
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.
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Implements TMVA::Node.
Definition at line 131 of file DecisionTreeNode.h.
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Reimplemented from TMVA::Node.
Definition at line 281 of file DecisionTreeNode.h.
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Definition at line 319 of file DecisionTreeNode.h.
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Definition at line 313 of file DecisionTreeNode.h.
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Reimplemented from TMVA::Node.
Definition at line 283 of file DecisionTreeNode.h.
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Reimplemented from TMVA::Node.
Definition at line 282 of file DecisionTreeNode.h.
Definition at line 181 of file DecisionTreeNode.h.
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.
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.
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Definition at line 149 of file DecisionTreeNode.h.
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Definition at line 299 of file DecisionTreeNode.h.
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Definition at line 328 of file DecisionTreeNode.h.
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Definition at line 329 of file DecisionTreeNode.h.
test event if it descends the tree at this node to the left
Implements TMVA::Node.
Definition at line 179 of file DecisionTreeNode.cxx.
test event if it descends the tree at this node to the right
Implements TMVA::Node.
Definition at line 155 of file DecisionTreeNode.cxx.
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Definition at line 336 of file DecisionTreeNode.h.
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Definition at line 540 of file DecisionTreeNode.cxx.
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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.
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recursively print the node and its daughters (–> print the 'tree')
Implements TMVA::Node.
Definition at line 241 of file DecisionTreeNode.cxx.
void TMVA::DecisionTreeNode::PrintRecPrune | ( | std::ostream & | os | ) | const |
recursive printout of the node and its daughters
Definition at line 393 of file DecisionTreeNode.cxx.
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Implements TMVA::Node.
Definition at line 455 of file DecisionTreeNode.cxx.
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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.
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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.
Definition at line 304 of file DecisionTreeNode.h.
Definition at line 308 of file DecisionTreeNode.h.
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Definition at line 157 of file DecisionTreeNode.h.
Definition at line 152 of file DecisionTreeNode.h.
set fisher coefficients
Definition at line 515 of file DecisionTreeNode.cxx.
Reimplemented from TMVA::Node.
Definition at line 286 of file DecisionTreeNode.h.
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Reimplemented from TMVA::Node.
Definition at line 288 of file DecisionTreeNode.h.
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.
Definition at line 172 of file DecisionTreeNode.h.
Reimplemented from TMVA::Node.
Definition at line 287 of file DecisionTreeNode.h.
Definition at line 178 of file DecisionTreeNode.h.
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.
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.
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Definition at line 364 of file DecisionTreeNode.h.
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flag to set node as terminal (i.e., without deleting its descendants)
Definition at line 373 of file DecisionTreeNode.h.