#include <shark/Models/Trees/CARTClassifier.h>

Inheritance diagram for shark::CARTClassifier< LabelType >:

Classes
struct	NodeInfo

Public Types
typedef base_type::BatchInputType	BatchInputType

typedef base_type::BatchOutputType	BatchOutputType

typedef std::vector< NodeInfo >	TreeType

Public Types inherited from shark::AbstractModel< RealVector, LabelType >
enum	Feature

typedef RealVector	InputType
	Defines the input type of the model. More...

typedef LabelType	OutputType
	Defines the output type of the model. More...

typedef Batch< InputType >::type	BatchInputType
	defines the batch type of the input type. More...

typedef Batch< OutputType >::type	BatchOutputType
	defines the batch type of the output type More...

typedef TypedFlags< Feature >	Features

typedef TypedFeatureNotAvailableException< Feature >	FeatureNotAvailableException

Public Member Functions
	CARTClassifier ()
	Constructor. More...

	CARTClassifier (TreeType const &tree)
	Constructor taking the tree as argument. More...

	CARTClassifier (TreeType &&tree)

	CARTClassifier (TreeType const &tree, bool optimize)
	Constructor taking the tree as argument and optimize it if requested. More...

	CARTClassifier (TreeType const &tree, std::size_t d)
	Constructor taking the tree as argument as well as maximum number of attributes. More...

	CARTClassifier (TreeType &&tree, std::size_t d) BOOST_NOEXCEPT_IF((std

std::string	name () const
	From INameable: return the class name. More...

boost::shared_ptr< State >	createState () const
	Creates an internal state of the model. More...

void	eval (BatchInputType const &patterns, BatchOutputType &outputs) const
	Evaluate the Tree on a batch of patterns. More...

void	eval (BatchInputType const &patterns, BatchOutputType &outputs, State &state) const
	Standard interface for evaluating the response of the model to a batch of patterns. More...

void	eval (RealVector const &pattern, LabelType &output)
	Evaluate the Tree on a single pattern. More...

void	setTree (TreeType const &tree)
	Set the model tree. More...

TreeType	getTree () const
	Get the model tree. More...

std::size_t	numberOfParameters () const
	The model does not have any parameters. More...

RealVector	parameterVector () const
	The model does not have any parameters. More...

void	setParameterVector (RealVector const &param)
	The model does not have any parameters. More...

void	read (InArchive &archive)
	from ISerializable, reads a model from an archive More...

void	write (OutArchive &archive) const
	from ISerializable, writes a model to an archive More...

UIntVector	countAttributes () const

std::size_t	inputSize () const
	Return input dimension. More...

void	setInputDimension (std::size_t d)

void	computeOOBerror (const ClassificationDataset &dataOOB)
	Compute oob error, given an oob dataset (Classification) More...

void	computeOOBerror (RegressionDataset const &dataOOB)
	Compute oob error, given an oob dataset (Regression) More...

double	OOBerror () const
	Return OOB error. More...

RealVector const &	featureImportances () const
	Return feature importances. More...

void	computeFeatureImportances (ClassificationDataset const &dataOOB, random::rng_type &rng)
	Compute feature importances, given an oob dataset (Classification) More...

void	computeFeatureImportances (RegressionDataset const &dataOOB, random::rng_type &rng)
	Compute feature importances, given an oob dataset (Regression) More...

Public Member Functions inherited from shark::AbstractModel< RealVector, LabelType >
	AbstractModel ()

virtual	~AbstractModel ()

const Features &	features () const

virtual void	updateFeatures ()

bool	hasFirstParameterDerivative () const
	Returns true when the first parameter derivative is implemented. More...

bool	hasSecondParameterDerivative () const
	Returns true when the second parameter derivative is implemented. More...

bool	hasFirstInputDerivative () const
	Returns true when the first input derivative is implemented. More...

bool	hasSecondInputDerivative () const
	Returns true when the second parameter derivative is implemented. More...

bool	isSequential () const

virtual void	eval (InputType const &pattern, OutputType &output) const
	Standard interface for evaluating the response of the model to a single pattern. More...

Data< OutputType >	operator() (Data< InputType > const &patterns) const
	Model evaluation as an operator for a whole dataset. This is a convenience function. More...

OutputType	operator() (InputType const &pattern) const
	Model evaluation as an operator for a single pattern. This is a convenience function. More...

BatchOutputType	operator() (BatchInputType const &patterns) const
	Model evaluation as an operator for a single pattern. This is a convenience function. More...

virtual void	weightedParameterDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, RealVector &derivative) const
	calculates the weighted sum of derivatives w.r.t the parameters. More...

virtual void	weightedParameterDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, Batch< RealMatrix >::type const &errorHessian, State const &state, RealVector &derivative, RealMatrix &hessian) const
	calculates the weighted sum of derivatives w.r.t the parameters More...

virtual void	weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, State const &state, BatchInputType &derivative) const
	calculates the weighted sum of derivatives w.r.t the inputs More...

virtual void	weightedInputDerivative (BatchInputType const &pattern, BatchOutputType const &coefficients, typename Batch< RealMatrix >::type const &errorHessian, State const &state, RealMatrix &derivative, Batch< RealMatrix >::type &hessian) const
	calculates the weighted sum of derivatives w.r.t the inputs More...

virtual void	weightedDerivatives (BatchInputType const &patterns, BatchOutputType const &coefficients, State const &state, RealVector &parameterDerivative, BatchInputType &inputDerivative) const
	calculates weighted input and parameter derivative at the same time More...

Public Member Functions inherited from shark::IParameterizable
virtual	~IParameterizable ()

Public Member Functions inherited from shark::INameable
virtual	~INameable ()

Public Member Functions inherited from shark::ISerializable
virtual	~ISerializable ()
	Virtual d'tor. More...

void	load (InArchive &archive, unsigned int version)
	Versioned loading of components, calls read(...). More...

void	save (OutArchive &archive, unsigned int version) const
	Versioned storing of components, calls write(...). More...

	BOOST_SERIALIZATION_SPLIT_MEMBER ()

Protected Member Functions
std::size_t	findNode (std::size_t nodeId) const
	Finds the index of the node with a certain nodeID in an unoptimized tree. More...

void	optimizeTree (TreeType &tree) const

template<class Vector >
LabelType const &	evalPattern (Vector const &pattern) const
	Evaluate the CART tree on a single sample. More...

Protected Attributes
TreeType	m_tree
	tree of the model More...

std::size_t	m_inputDimension
	Number of attributes (set by trainer) More...

RealVector	m_featureImportances

double	m_OOBerror

Protected Attributes inherited from shark::AbstractModel< RealVector, LabelType >
Features	m_features

Detailed Description

template<class LabelType>
class shark::CARTClassifier< LabelType >

CART Classifier.

: The CARTClassifier predicts a class label using the CART algorithm.

: It is a decision tree algorithm.

Definition at line 58 of file CARTClassifier.h.

Member Typedef Documentation

◆ BatchInputType

template<class LabelType>

typedef base_type::BatchInputType shark::CARTClassifier< LabelType >::BatchInputType

Definition at line 63 of file CARTClassifier.h.

◆ BatchOutputType

template<class LabelType>

typedef base_type::BatchOutputType shark::CARTClassifier< LabelType >::BatchOutputType

Definition at line 64 of file CARTClassifier.h.

◆ TreeType

template<class LabelType>

typedef std::vector<NodeInfo> shark::CARTClassifier< LabelType >::TreeType

Vector of structs that contains the splitting information and the labels. The class label is a normalized histogram in the classification case. In the regression case, the label is the regression value.

Definition at line 121 of file CARTClassifier.h.

Constructor & Destructor Documentation

◆ CARTClassifier() [1/6]

template<class LabelType>

shark::CARTClassifier< LabelType >::CARTClassifier ( )

inline

Constructor.

Definition at line 124 of file CARTClassifier.h.

◆ CARTClassifier() [2/6]

template<class LabelType>

shark::CARTClassifier< LabelType >::CARTClassifier ( TreeType const & tree )

inlineexplicit

Constructor taking the tree as argument.

Definition at line 128 of file CARTClassifier.h.

◆ CARTClassifier() [3/6]

template<class LabelType>

shark::CARTClassifier< LabelType >::CARTClassifier ( TreeType && tree )

inlineexplicit

Definition at line 131 of file CARTClassifier.h.

◆ CARTClassifier() [4/6]

template<class LabelType>

shark::CARTClassifier< LabelType >::CARTClassifier	(	TreeType const &	tree,
		bool	optimize
	)

inline

Constructor taking the tree as argument and optimize it if requested.

Definition at line 136 of file CARTClassifier.h.

◆ CARTClassifier() [5/6]

template<class LabelType>

shark::CARTClassifier< LabelType >::CARTClassifier	(	TreeType const &	tree,
		std::size_t	d
	)

inline

Constructor taking the tree as argument as well as maximum number of attributes.

Definition at line 145 of file CARTClassifier.h.

◆ CARTClassifier() [6/6]

template<class LabelType>

shark::CARTClassifier< LabelType >::CARTClassifier	(	TreeType &&	tree,
		std::size_t	d
	)

inline

Definition at line 151 of file CARTClassifier.h.

Member Function Documentation

◆ computeFeatureImportances() [1/2]

template<class LabelType>

void shark::CARTClassifier< LabelType >::computeFeatureImportances	(	ClassificationDataset const &	dataOOB,
		random::rng_type &	rng
	)

inline

Compute feature importances, given an oob dataset (Classification)

Definition at line 284 of file CARTClassifier.h.

◆ computeFeatureImportances() [2/2]

template<class LabelType>

void shark::CARTClassifier< LabelType >::computeFeatureImportances	(	RegressionDataset const &	dataOOB,
		random::rng_type &	rng
	)

inline

Compute feature importances, given an oob dataset (Regression)

Definition at line 319 of file CARTClassifier.h.

◆ computeOOBerror() [1/2]

template<class LabelType>

void shark::CARTClassifier< LabelType >::computeOOBerror ( const ClassificationDataset & dataOOB )

inline

Compute oob error, given an oob dataset (Classification)

Definition at line 250 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::computeFeatureImportances().

◆ computeOOBerror() [2/2]

template<class LabelType>

void shark::CARTClassifier< LabelType >::computeOOBerror ( RegressionDataset const & dataOOB )

inline

Compute oob error, given an oob dataset (Regression)

Definition at line 262 of file CARTClassifier.h.

◆ countAttributes()

template<class LabelType>

UIntVector shark::CARTClassifier< LabelType >::countAttributes ( ) const

inline

Definition at line 226 of file CARTClassifier.h.

◆ createState()

template<class LabelType>

boost::shared_ptr<State> shark::CARTClassifier< LabelType >::createState ( ) const

inlinevirtual

Creates an internal state of the model.

The state is needed when the derivatives are to be calculated. Eval can store a state which is then reused to speed up the calculations of the derivatives. This also allows eval to be evaluated in parallel!

Reimplemented from shark::AbstractModel< RealVector, LabelType >.

Definition at line 161 of file CARTClassifier.h.

◆ eval() [1/3]

template<class LabelType>

void shark::CARTClassifier< LabelType >::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs
	)		const

inlinevirtual

Evaluate the Tree on a batch of patterns.

Reimplemented from shark::AbstractModel< RealVector, LabelType >.

Definition at line 167 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::eval().

◆ eval() [2/3]

template<class LabelType>

void shark::CARTClassifier< LabelType >::eval	(	BatchInputType const &	patterns,
		BatchOutputType &	outputs,
		State &	state
	)		const

inlinevirtual

Standard interface for evaluating the response of the model to a batch of patterns.

Parameters

patterns	the inputs of the model
outputs	the predictions or response of the model to every pattern
state	intermediate results stored by eval which can be reused for derivative computation.

Implements shark::AbstractModel< RealVector, LabelType >.

Definition at line 180 of file CARTClassifier.h.

◆ eval() [3/3]

template<class LabelType>

void shark::CARTClassifier< LabelType >::eval	(	RealVector const &	pattern,
		LabelType &	output
	)

inline

Evaluate the Tree on a single pattern.

Definition at line 184 of file CARTClassifier.h.

◆ evalPattern()

template<class LabelType>

template<class Vector >

LabelType const& shark::CARTClassifier< LabelType >::evalPattern ( Vector const & pattern ) const

inlineprotected

Evaluate the CART tree on a single sample.

Definition at line 380 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::eval().

◆ featureImportances()

template<class LabelType>

RealVector const& shark::CARTClassifier< LabelType >::featureImportances ( ) const

inline

Return feature importances.

Definition at line 279 of file CARTClassifier.h.

◆ findNode()

template<class LabelType>

std::size_t shark::CARTClassifier< LabelType >::findNode ( std::size_t nodeId ) const

inlineprotected

Finds the index of the node with a certain nodeID in an unoptimized tree.

Definition at line 358 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::optimizeTree().

◆ getTree()

template<class LabelType>

TreeType shark::CARTClassifier< LabelType >::getTree ( ) const

inline

Get the model tree.

Definition at line 195 of file CARTClassifier.h.

◆ inputSize()

template<class LabelType>

std::size_t shark::CARTClassifier< LabelType >::inputSize ( ) const

inline

Return input dimension.

Definition at line 240 of file CARTClassifier.h.

◆ name()

template<class LabelType>

std::string shark::CARTClassifier< LabelType >::name ( ) const

inlinevirtual

From INameable: return the class name.

Reimplemented from shark::INameable.

Definition at line 158 of file CARTClassifier.h.

◆ numberOfParameters()

template<class LabelType>

std::size_t shark::CARTClassifier< LabelType >::numberOfParameters ( ) const

inlinevirtual

The model does not have any parameters.

Reimplemented from shark::IParameterizable.

Definition at line 200 of file CARTClassifier.h.

◆ OOBerror()

template<class LabelType>

double shark::CARTClassifier< LabelType >::OOBerror ( ) const

inline

Return OOB error.

Definition at line 274 of file CARTClassifier.h.

◆ optimizeTree()

template<class LabelType>

void shark::CARTClassifier< LabelType >::optimizeTree ( TreeType & tree ) const

inlineprotected

Optimize a tree, so constant lookup can be used. The optimization is done by changing the index of the children to use indices instead of node ID. Furthermore, the node IDs are converted to index numbers.

Definition at line 368 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::CARTClassifier(), and shark::CARTClassifier< RealVector >::setTree().

◆ parameterVector()

template<class LabelType>

RealVector shark::CARTClassifier< LabelType >::parameterVector ( ) const

inlinevirtual

The model does not have any parameters.

Reimplemented from shark::IParameterizable.

Definition at line 205 of file CARTClassifier.h.

◆ read()

template<class LabelType>

void shark::CARTClassifier< LabelType >::read ( InArchive & archive )

inlinevirtual

from ISerializable, reads a model from an archive

Reimplemented from shark::AbstractModel< RealVector, LabelType >.

Definition at line 215 of file CARTClassifier.h.

◆ setInputDimension()

template<class LabelType>

void shark::CARTClassifier< LabelType >::setInputDimension ( std::size_t d )

inline

Definition at line 245 of file CARTClassifier.h.

◆ setParameterVector()

template<class LabelType>

void shark::CARTClassifier< LabelType >::setParameterVector ( RealVector const & param )

inlinevirtual

The model does not have any parameters.

Reimplemented from shark::IParameterizable.

Definition at line 210 of file CARTClassifier.h.

◆ setTree()

template<class LabelType>

void shark::CARTClassifier< LabelType >::setTree ( TreeType const & tree )

inline

Set the model tree.

Definition at line 189 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::CARTClassifier().

◆ write()

template<class LabelType>

void shark::CARTClassifier< LabelType >::write ( OutArchive & archive ) const

inlinevirtual

from ISerializable, writes a model to an archive

Reimplemented from shark::AbstractModel< RealVector, LabelType >.

Definition at line 220 of file CARTClassifier.h.

Member Data Documentation

◆ m_featureImportances

template<class LabelType>

RealVector shark::CARTClassifier< LabelType >::m_featureImportances

protected

Definition at line 399 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::computeFeatureImportances(), and shark::CARTClassifier< RealVector >::featureImportances().

◆ m_inputDimension

template<class LabelType>

std::size_t shark::CARTClassifier< LabelType >::m_inputDimension

protected

Number of attributes (set by trainer)

Definition at line 396 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::CARTClassifier(), shark::CARTClassifier< RealVector >::computeFeatureImportances(), shark::CARTClassifier< RealVector >::countAttributes(), shark::CARTClassifier< RealVector >::inputSize(), and shark::CARTClassifier< RealVector >::setInputDimension().

◆ m_OOBerror

template<class LabelType>

double shark::CARTClassifier< LabelType >::m_OOBerror

protected

Definition at line 402 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::CARTClassifier(), shark::CARTClassifier< RealVector >::computeFeatureImportances(), shark::CARTClassifier< RealVector >::computeOOBerror(), and shark::CARTClassifier< RealVector >::OOBerror().

◆ m_tree

template<class LabelType>

TreeType shark::CARTClassifier< LabelType >::m_tree

protected

tree of the model

Definition at line 355 of file CARTClassifier.h.

Referenced by shark::CARTClassifier< RealVector >::CARTClassifier(), shark::CARTClassifier< RealVector >::countAttributes(), shark::CARTClassifier< RealVector >::getTree(), shark::CARTClassifier< RealVector >::read(), shark::CARTClassifier< RealVector >::setTree(), and shark::CARTClassifier< RealVector >::write().

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

include/shark/Models/Trees/CARTClassifier.h

Classes

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

template<class LabelType> class shark::CARTClassifier< LabelType >

Member Typedef Documentation

◆ BatchInputType

◆ BatchOutputType

◆ TreeType

Constructor & Destructor Documentation

◆ CARTClassifier() [1/6]

◆ CARTClassifier() [2/6]

◆ CARTClassifier() [3/6]

◆ CARTClassifier() [4/6]

◆ CARTClassifier() [5/6]

◆ CARTClassifier() [6/6]

Member Function Documentation

◆ computeFeatureImportances() [1/2]

◆ computeFeatureImportances() [2/2]

◆ computeOOBerror() [1/2]

◆ computeOOBerror() [2/2]

◆ countAttributes()

◆ createState()

◆ eval() [1/3]

◆ eval() [2/3]

◆ eval() [3/3]

◆ evalPattern()

◆ featureImportances()

◆ findNode()

◆ getTree()

◆ inputSize()

◆ name()

◆ numberOfParameters()

◆ OOBerror()

◆ optimizeTree()

◆ parameterVector()

◆ read()

◆ setInputDimension()

◆ setParameterVector()

◆ setTree()

◆ write()

Member Data Documentation

◆ m_featureImportances

◆ m_inputDimension

◆ m_OOBerror

◆ m_tree

template<class LabelType>
class shark::CARTClassifier< LabelType >