lar_content::AdaBoostDecisionTree::WeakClassifier Class Reference

WeakClassifier class containing a decision tree and a weight. More...

Public Member Functions
	WeakClassifier (const pandora::TiXmlHandle *const pXmlHandle)
	Constructor using xml handle to set member variables. More...
	WeakClassifier (const WeakClassifier &rhs)
	Copy constructor. More...
WeakClassifier &	operator= (const WeakClassifier &rhs)
	Assignment operator. More...
	~WeakClassifier ()
	Destructor. More...
bool	Predict (const LArMvaHelper::MvaFeatureVector &features) const
	Predict signal or background based on trained data. More...
bool	EvaluateNode (const int nodeId, const LArMvaHelper::MvaFeatureVector &features) const
	Evalute node and return outcome. More...
double	GetWeight () const
	Get boost weight for weak classifier. More...
int	GetTreeId () const
	Get tree id for weak classifier. More...

Private Attributes
IdToNodeMap	m_idToNodeMap
	Decision tree nodes. More...
double	m_weight
	Boost weight. More...
int	m_treeId
	Decision tree id. More...

Detailed Description

WeakClassifier class containing a decision tree and a weight.

Definition at line 196 of file LArAdaBoostDecisionTree.h.

Constructor & Destructor Documentation

lar_content::AdaBoostDecisionTree::WeakClassifier::WeakClassifier

(

const pandora::TiXmlHandle *const

pXmlHandle

)

Constructor using xml handle to set member variables.

Parameters

pXmlHandle

xml handle to use when setting member variables

Referenced by lar_content::AdaBoostDecisionTree::StrongClassifier::operator=(), lar_content::AdaBoostDecisionTree::StrongClassifier::ReadComponent(), lar_content::AdaBoostDecisionTree::StrongClassifier::StrongClassifier(), and lar_content::AdaBoostDecisionTree::Node::~Node().

lar_content::AdaBoostDecisionTree::WeakClassifier::WeakClassifier

(

const WeakClassifier &

rhs

)

Copy constructor.

Parameters

rhs	the weak classifier to copy

Definition at line 290 of file LArAdaBoostDecisionTree.cc.

References lar_content::AdaBoostDecisionTree::Node::GetNodeId(), and m_idToNodeMap.

                                                                            :
    m_weight(rhs.m_weight),
    m_treeId(rhs.m_treeId)
{
    for (const auto &mapEntry : rhs.m_idToNodeMap)
    {
        const Node *pNode = new Node(*(mapEntry.second));
        m_idToNodeMap.insert(IdToNodeMap::value_type(pNode->GetNodeId(), pNode));
    }
}

lar_content::AdaBoostDecisionTree::WeakClassifier::~WeakClassifier

(

)

Destructor.

Definition at line 322 of file LArAdaBoostDecisionTree.cc.

References m_idToNodeMap.

{
    for (const auto &mapEntry : m_idToNodeMap)
        delete mapEntry.second;
}

Member Function Documentation

bool lar_content::AdaBoostDecisionTree::WeakClassifier::EvaluateNode	(	const int	nodeId,
		const LArMvaHelper::MvaFeatureVector &	features
	)		const

Evalute node and return outcome.

Parameters

nodeId	current node id
features	the input features

Returns

is signal or background node

Definition at line 337 of file LArAdaBoostDecisionTree.cc.

References Get, lar_content::AdaBoostDecisionTree::Node::GetLeftChildNodeId(), lar_content::AdaBoostDecisionTree::Node::GetOutcome(), lar_content::AdaBoostDecisionTree::Node::GetRightChildNodeId(), lar_content::AdaBoostDecisionTree::Node::GetThreshold(), lar_content::AdaBoostDecisionTree::Node::GetVariableId(), lar_content::AdaBoostDecisionTree::Node::IsLeaf(), m_idToNodeMap, and lar_content::AdaBoostDecisionTree::StrongClassifier::StrongClassifier().

Referenced by Predict().

{
    const Node *pActiveNode(nullptr);

    if (m_idToNodeMap.find(nodeId) != m_idToNodeMap.end())
    {
        pActiveNode = m_idToNodeMap.at(nodeId);
    }
    else
    {
        throw StatusCodeException(STATUS_CODE_OUT_OF_RANGE);
    }

    if (pActiveNode->IsLeaf())
        return pActiveNode->GetOutcome();

    if (static_cast<int>(features.size()) <= pActiveNode->GetVariableId())
        throw StatusCodeException(STATUS_CODE_NOT_FOUND);

    if (features.at(pActiveNode->GetVariableId()).Get() <= pActiveNode->GetThreshold())
    {
        return this->EvaluateNode(pActiveNode->GetLeftChildNodeId(), features);
    }
    else
    {
        return this->EvaluateNode(pActiveNode->GetRightChildNodeId(), features);
    }
}

int lar_content::AdaBoostDecisionTree::WeakClassifier::GetTreeId ( ) const

inline

Get tree id for weak classifier.

Returns

tree id

Definition at line 393 of file LArAdaBoostDecisionTree.h.

{
    return m_treeId;
}

double lar_content::AdaBoostDecisionTree::WeakClassifier::GetWeight ( ) const

inline

Get boost weight for weak classifier.

Returns

weight for decision tree

Definition at line 386 of file LArAdaBoostDecisionTree.h.

{
    return m_weight;
}

AdaBoostDecisionTree::WeakClassifier & lar_content::AdaBoostDecisionTree::WeakClassifier::operator=

(

const WeakClassifier &

rhs

)

Assignment operator.

Parameters

rhs	the weak classifier to assign

Definition at line 303 of file LArAdaBoostDecisionTree.cc.

References lar_content::AdaBoostDecisionTree::Node::GetNodeId(), m_idToNodeMap, m_treeId, and m_weight.

{
    if (this != &rhs)
    {
        for (const auto &mapEntry : rhs.m_idToNodeMap)
        {
            const Node *pNode = new Node(*(mapEntry.second));
            m_idToNodeMap.insert(IdToNodeMap::value_type(pNode->GetNodeId(), pNode));
        }

        m_weight = rhs.m_weight;
        m_treeId = rhs.m_treeId;
    }

    return *this;
}

bool lar_content::AdaBoostDecisionTree::WeakClassifier::Predict

(

const LArMvaHelper::MvaFeatureVector &

features

)

const

Predict signal or background based on trained data.

Parameters

features

the input features

Returns

is signal or background

Definition at line 330 of file LArAdaBoostDecisionTree.cc.

References EvaluateNode().

{
    return this->EvaluateNode(0, features);
}

Member Data Documentation

IdToNodeMap lar_content::AdaBoostDecisionTree::WeakClassifier::m_idToNodeMap

private

Decision tree nodes.

Definition at line 259 of file LArAdaBoostDecisionTree.h.

Referenced by EvaluateNode(), operator=(), WeakClassifier(), and ~WeakClassifier().

int lar_content::AdaBoostDecisionTree::WeakClassifier::m_treeId

private

Decision tree id.

Definition at line 261 of file LArAdaBoostDecisionTree.h.

Referenced by operator=().

double lar_content::AdaBoostDecisionTree::WeakClassifier::m_weight

private

Boost weight.

Definition at line 260 of file LArAdaBoostDecisionTree.h.

Referenced by operator=().

---

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

• larpandoracontent/v04_08_01/source/larpandoracontent/LArObjects/LArAdaBoostDecisionTree.h
• larpandoracontent/v04_08_01/source/larpandoracontent/LArObjects/LArAdaBoostDecisionTree.cc