Definition at line 71 of file CostComplexityPruneTool.h.

Public Member Functions
	CostComplexityPruneTool (SeparationBase *qualityIndex=NULL)
	the constructor for the cost complexity prunig More...

virtual	~CostComplexityPruneTool ()
	the destructor for the cost complexity prunig More...

virtual PruningInfo *	CalculatePruningInfo (DecisionTree dt, const IPruneTool::EventSample testEvents=NULL, Bool_t isAutomatic=kFALSE)

Public Member Functions inherited from TMVA::IPruneTool
	IPruneTool ()

virtual	~IPruneTool ()

void	SetPruneStrength (Double_t alpha)

Double_t	GetPruneStrength () const

void	SetAutomatic ()

Bool_t	IsAutomatic () const

Private Member Functions
void	InitTreePruningMetaData (DecisionTreeNode *n)
	the optimal index of the prune sequence More...

void	Optimize (DecisionTree *dt, Double_t weights)
	after the critical alpha values (at which the corresponding nodes would be pruned away) had been established in the "InitMetaData" we need now: automatic pruning: find the value of "alpha" for which the test sample gives minimal error, on the tree with all nodes pruned that have alpha_critital < alpha, fixed parameter pruning More...

MsgLogger &	Log () const
	output stream to save logging information More...

Private Attributes
SeparationBase *	fQualityIndexTool

std::vector< DecisionTreeNode * >	fPruneSequence
	the quality index used to calculate R(t), R(T) = sum[t in ~T]{ R(t) } More...

std::vector< Double_t >	fPruneStrengthList
	map of weakest links (i.e., branches to prune) -> pruning index More...

std::vector< Double_t >	fQualityIndexList
	map of alpha -> pruning index More...

Int_t	fOptimalK
	map of R(T) -> pruning index More...

MsgLogger *	fLogger

Additional Inherited Members
Public Types inherited from TMVA::IPruneTool
typedef std::vector< const Event * >	EventSample

Protected Attributes inherited from TMVA::IPruneTool
Double_t	fPruneStrength

Double_t	S
	regularization parameter in pruning More...

Double_t	B

#include <TMVA/CostComplexityPruneTool.h>

Inheritance diagram for TMVA::CostComplexityPruneTool:

[legend]

Constructor & Destructor Documentation

CostComplexityPruneTool::CostComplexityPruneTool ( SeparationBase * qualityIndex = NULL )

the constructor for the cost complexity prunig

Definition at line 45 of file CostComplexityPruneTool.cxx.

CostComplexityPruneTool::~CostComplexityPruneTool ( )

virtual

the destructor for the cost complexity prunig

Definition at line 66 of file CostComplexityPruneTool.cxx.

Member Function Documentation

PruningInfo * CostComplexityPruneTool::CalculatePruningInfo	(	DecisionTree *	dt,
		const IPruneTool::EventSample *	testEvents = `NULL`,
		Bool_t	isAutomatic = `kFALSE`
	)

virtual

Implements TMVA::IPruneTool.

Definition at line 73 of file CostComplexityPruneTool.cxx.

void CostComplexityPruneTool::InitTreePruningMetaData ( DecisionTreeNode * n )

private

the optimal index of the prune sequence

initialise "meta data" for the pruning, like the "costcomplexity", the critical alpha, the minimal alpha down the tree, etc...

for each node!!

Definition at line 159 of file CostComplexityPruneTool.cxx.

Referenced by CalculatePruningInfo().

MsgLogger& TMVA::CostComplexityPruneTool::Log ( ) const

inlineprivate

output stream to save logging information

Definition at line 96 of file CostComplexityPruneTool.h.

Referenced by CalculatePruningInfo(), and Optimize().

void CostComplexityPruneTool::Optimize	(	DecisionTree *	dt,
		Double_t	weights
	)

private

after the critical alpha values (at which the corresponding nodes would be pruned away) had been established in the "InitMetaData" we need now: automatic pruning: find the value of "alpha" for which the test sample gives minimal error, on the tree with all nodes pruned that have alpha_critital < alpha, fixed parameter pruning

Definition at line 213 of file CostComplexityPruneTool.cxx.

Referenced by CalculatePruningInfo().