lar_content::AdaBoostDecisionTree Class Reference

AdaBoostDecisionTree class. More...

#include "LArAdaBoostDecisionTree.h"

Inheritance diagram for lar_content::AdaBoostDecisionTree:

Collaboration diagram for lar_content::AdaBoostDecisionTree:

Classes
class	Node
	Node class used for representing a decision tree. More...
class	StrongClassifier
	StrongClassifier class used in application of adaptive boost decision tree. More...
class	WeakClassifier
	WeakClassifier class containing a decision tree and a weight. More...

Public Member Functions
	AdaBoostDecisionTree ()
	Constructor.
	AdaBoostDecisionTree (const AdaBoostDecisionTree &rhs)
	Copy constructor.
AdaBoostDecisionTree &	operator= (const AdaBoostDecisionTree &rhs)
	Assignment operator.
	~AdaBoostDecisionTree ()
	Destructor.
pandora::StatusCode	Initialize (const std::string &parameterLocation, const std::string &bdtName)
	Initialize the bdt model.
bool	Classify (const LArMvaHelper::MvaFeatureVector &features) const
	Classify the set of input features based on the trained model.
double	CalculateClassificationScore (const LArMvaHelper::MvaFeatureVector &features) const
	Calculate the classification score for a set of input features, based on the trained model.
double	CalculateProbability (const LArMvaHelper::MvaFeatureVector &features) const
	Calculate the classification probability for a set of input features, based on the trained model.

Private Types
typedef std::map< int, const Node * >	IdToNodeMap
typedef std::vector< const WeakClassifier * >	WeakClassifiers

Private Member Functions
double	CalculateScore (const LArMvaHelper::MvaFeatureVector &features) const
	Calculate score for input features using strong classifier.

Private Attributes
StrongClassifier *	m_pStrongClassifier
	Strong adaptive boost tree classifier.

Detailed Description

AdaBoostDecisionTree class.

Definition at line 27 of file LArAdaBoostDecisionTree.h.

Member Typedef Documentation

IdToNodeMap

typedef std::map<int, const Node *> lar_content::AdaBoostDecisionTree::IdToNodeMap

private

Definition at line 191 of file LArAdaBoostDecisionTree.h.

WeakClassifiers

typedef std::vector<const WeakClassifier *> lar_content::AdaBoostDecisionTree::WeakClassifiers

private

Definition at line 264 of file LArAdaBoostDecisionTree.h.

Constructor & Destructor Documentation

AdaBoostDecisionTree() [1/2]

lar_content::AdaBoostDecisionTree::AdaBoostDecisionTree

(

)

Constructor.

Definition at line 18 of file LArAdaBoostDecisionTree.cc.

AdaBoostDecisionTree() [2/2]

lar_content::AdaBoostDecisionTree::AdaBoostDecisionTree

(

const AdaBoostDecisionTree &

rhs

)

Copy constructor.

Parameters

rhs	the AdaBoostDecisionTree to copy

Definition at line 24 of file LArAdaBoostDecisionTree.cc.

~AdaBoostDecisionTree()

lar_content::AdaBoostDecisionTree::~AdaBoostDecisionTree

(

)

Destructor.

Definition at line 41 of file LArAdaBoostDecisionTree.cc.

Member Function Documentation

CalculateClassificationScore()

double lar_content::AdaBoostDecisionTree::CalculateClassificationScore ( const LArMvaHelper::MvaFeatureVector &  features ) const

virtual

Calculate the classification score for a set of input features, based on the trained model.

Parameters

features

the input features

Returns

the classification score

Implements lar_content::MvaInterface.

Definition at line 126 of file LArAdaBoostDecisionTree.cc.

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CalculateProbability()

double lar_content::AdaBoostDecisionTree::CalculateProbability ( const LArMvaHelper::MvaFeatureVector &  features ) const

virtual

Calculate the classification probability for a set of input features, based on the trained model.

Parameters

features

the input features

Returns

the classification probability

Implements lar_content::MvaInterface.

Definition at line 133 of file LArAdaBoostDecisionTree.cc.

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CalculateScore()

double lar_content::AdaBoostDecisionTree::CalculateScore ( const LArMvaHelper::MvaFeatureVector &  features ) const

private

Calculate score for input features using strong classifier.

Parameters

features

the input features

Returns

score

Definition at line 142 of file LArAdaBoostDecisionTree.cc.

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Classify()

bool lar_content::AdaBoostDecisionTree::Classify ( const LArMvaHelper::MvaFeatureVector &  features ) const

virtual

Classify the set of input features based on the trained model.

Parameters

features

the input features

Returns

the classification

Implements lar_content::MvaInterface.

Definition at line 119 of file LArAdaBoostDecisionTree.cc.

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Initialize()

StatusCode lar_content::AdaBoostDecisionTree::Initialize	(	const std::string &	parameterLocation,
		const std::string &	bdtName
	)

Initialize the bdt model.

Parameters

parameterLocation	the location of the model
bdtName	the name of the model

Returns

success

Definition at line 48 of file LArAdaBoostDecisionTree.cc.

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operator=()

AdaBoostDecisionTree & lar_content::AdaBoostDecisionTree::operator=

(

const AdaBoostDecisionTree &

rhs

)

Assignment operator.

Parameters

rhs	the AdaBoostDecisionTree to assign

Definition at line 31 of file LArAdaBoostDecisionTree.cc.

Member Data Documentation

m_pStrongClassifier

StrongClassifier* lar_content::AdaBoostDecisionTree::m_pStrongClassifier

private

Strong adaptive boost tree classifier.

Definition at line 325 of file LArAdaBoostDecisionTree.h.

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

• LArContent/larpandoracontent/LArObjects/LArAdaBoostDecisionTree.h
• LArContent/larpandoracontent/LArObjects/LArAdaBoostDecisionTree.cc