#include <ml.hpp>

Inheritance diagram for CvBoost:

Public Types
enum	{ DISCRETE =0, REAL =1, LOGIT =2, GENTLE =3 }

enum	{ DEFAULT =0, GINI =1, MISCLASS =3, SQERR =4 }

Public Member Functions
	CvBoost ()

virtual	~CvBoost ()

	CvBoost (const CvMat trainData, int tflag, const CvMat responses, const CvMat varIdx=0, const CvMat sampleIdx=0, const CvMat varType=0, const CvMat missingDataMask=0, CvBoostParams params=CvBoostParams())

virtual bool	train (const CvMat trainData, int tflag, const CvMat responses, const CvMat varIdx=0, const CvMat sampleIdx=0, const CvMat varType=0, const CvMat missingDataMask=0, CvBoostParams params=CvBoostParams(), bool update=false)

virtual bool	train (CvMLData *data, CvBoostParams params=CvBoostParams(), bool update=false)

virtual float	predict (const CvMat sample, const CvMat missing=0, CvMat *weak_responses=0, CvSlice slice=CV_WHOLE_SEQ, bool raw_mode=false, bool return_sum=false) const

	CvBoost (const cv::Mat &trainData, int tflag, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat(), const cv::Mat &varType=cv::Mat(), const cv::Mat &missingDataMask=cv::Mat(), CvBoostParams params=CvBoostParams())

virtual bool	train (const cv::Mat &trainData, int tflag, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat(), const cv::Mat &varType=cv::Mat(), const cv::Mat &missingDataMask=cv::Mat(), CvBoostParams params=CvBoostParams(), bool update=false)

virtual float	predict (const cv::Mat &sample, const cv::Mat &missing=cv::Mat(), const cv::Range &slice=cv::Range::all(), bool rawMode=false, bool returnSum=false) const

virtual float	calc_error (CvMLData _data, int type, std::vector< float > resp=0)

virtual void	prune (CvSlice slice)

virtual void	clear ()

virtual void	write (CvFileStorage storage, const char name) const

virtual void	read (CvFileStorage storage, CvFileNode node)

virtual const CvMat *	get_active_vars (bool absolute_idx=true)

CvSeq *	get_weak_predictors ()

CvMat *	get_weights ()

CvMat *	get_subtree_weights ()

CvMat *	get_weak_response ()

const CvBoostParams &	get_params () const

const CvDTreeTrainData *	get_data () const

Public Member Functions inherited from CvStatModel
	CvStatModel ()

virtual	~CvStatModel ()

virtual void	save (const char filename, const char name=0) const

virtual void	load (const char filename, const char name=0)

Protected Member Functions
void	update_weights_impl (CvBoostTree *tree, double initial_weights[2])

virtual bool	set_params (const CvBoostParams &params)

virtual void	update_weights (CvBoostTree *tree)

virtual void	trim_weights ()

virtual void	write_params (CvFileStorage *fs) const

virtual void	read_params (CvFileStorage fs, CvFileNode node)

Protected Attributes
CvDTreeTrainData *	data

CvBoostParams	params

CvSeq *	weak

CvMat *	active_vars

CvMat *	active_vars_abs

bool	have_active_cat_vars

CvMat *	orig_response

CvMat *	sum_response

CvMat *	weak_eval

CvMat *	subsample_mask

CvMat *	weights

CvMat *	subtree_weights

bool	have_subsample

Protected Attributes inherited from CvStatModel
const char *	default_model_name

Member Enumeration Documentation

§ anonymous enum

anonymous enum

Enumerator
DISCRETE
REAL
LOGIT
GENTLE

§ anonymous enum

anonymous enum

Enumerator
DEFAULT
GINI
MISCLASS
SQERR

Constructor & Destructor Documentation

§ CvBoost() [1/3]

CvBoost::CvBoost ( )

§ ~CvBoost()

virtual CvBoost::~CvBoost ( )

virtual

§ CvBoost() [2/3]

CvBoost::CvBoost	(	const CvMat *	trainData,
		int	tflag,
		const CvMat *	responses,
		const CvMat *	varIdx = `0`,
		const CvMat *	sampleIdx = `0`,
		const CvMat *	varType = `0`,
		const CvMat *	missingDataMask = `0`,
		CvBoostParams	params = `CvBoostParams()`
	)

§ CvBoost() [3/3]

CvBoost::CvBoost	(	const cv::Mat &	trainData,
		int	tflag,
		const cv::Mat &	responses,
		const cv::Mat &	varIdx = `cv::Mat()`,
		const cv::Mat &	sampleIdx = `cv::Mat()`,
		const cv::Mat &	varType = `cv::Mat()`,
		const cv::Mat &	missingDataMask = `cv::Mat()`,
		CvBoostParams	params = `CvBoostParams()`
	)

Member Function Documentation

§ calc_error()

virtual float CvBoost::calc_error	(	CvMLData *	_data,
		int	type,
		std::vector< float > *	resp = `0`
	)

virtual

§ clear()

virtual void CvBoost::clear ( )

virtual

Reimplemented from CvStatModel.

§ get_active_vars()

virtual const CvMat* CvBoost::get_active_vars ( bool absolute_idx = true )

virtual

§ get_data()

const CvDTreeTrainData* CvBoost::get_data ( ) const

§ get_params()

const CvBoostParams& CvBoost::get_params ( ) const

§ get_subtree_weights()

CvMat* CvBoost::get_subtree_weights ( )

§ get_weak_predictors()

CvSeq* CvBoost::get_weak_predictors ( )

§ get_weak_response()

CvMat* CvBoost::get_weak_response ( )

§ get_weights()

CvMat* CvBoost::get_weights ( )

§ predict() [1/2]

virtual float CvBoost::predict	(	const CvMat *	sample,
		const CvMat *	missing = `0`,
		CvMat *	weak_responses = `0`,
		CvSlice	slice = `CV_WHOLE_SEQ`,
		bool	raw_mode = `false`,
		bool	return_sum = `false`
	)		const

virtual

§ predict() [2/2]

virtual float CvBoost::predict	(	const cv::Mat &	sample,
		const cv::Mat &	missing = `cv::Mat()`,
		const cv::Range &	slice = `cv::Range::all()`,
		bool	rawMode = `false`,
		bool	returnSum = `false`
	)		const

virtual

§ prune()

virtual void CvBoost::prune ( CvSlice slice )

virtual

§ read()

virtual void CvBoost::read	(	CvFileStorage *	storage,
		CvFileNode *	node
	)

virtual

Reimplemented from CvStatModel.

§ read_params()

virtual void CvBoost::read_params	(	CvFileStorage *	fs,
		CvFileNode *	node
	)

protectedvirtual

§ set_params()

virtual bool CvBoost::set_params ( const CvBoostParams & params )

protectedvirtual

§ train() [1/3]

virtual bool CvBoost::train	(	const CvMat *	trainData,
		int	tflag,
		const CvMat *	responses,
		const CvMat *	varIdx = `0`,
		const CvMat *	sampleIdx = `0`,
		const CvMat *	varType = `0`,
		const CvMat *	missingDataMask = `0`,
		CvBoostParams	params = `CvBoostParams()`,
		bool	update = `false`
	)

virtual

§ train() [2/3]

virtual bool CvBoost::train	(	CvMLData *	data,
		CvBoostParams	params = `CvBoostParams()`,
		bool	update = `false`
	)

virtual

§ train() [3/3]

virtual bool CvBoost::train	(	const cv::Mat &	trainData,
		int	tflag,
		const cv::Mat &	responses,
		const cv::Mat &	varIdx = `cv::Mat()`,
		const cv::Mat &	sampleIdx = `cv::Mat()`,
		const cv::Mat &	varType = `cv::Mat()`,
		const cv::Mat &	missingDataMask = `cv::Mat()`,
		CvBoostParams	params = `CvBoostParams()`,
		bool	update = `false`
	)

virtual

§ trim_weights()

virtual void CvBoost::trim_weights ( )

protectedvirtual

§ update_weights()

virtual void CvBoost::update_weights ( CvBoostTree * tree )

protectedvirtual

§ update_weights_impl()

void CvBoost::update_weights_impl	(	CvBoostTree *	tree,
		double	initial_weights[2]
	)

protected

§ write()

virtual void CvBoost::write	(	CvFileStorage *	storage,
		const char *	name
	)		const

virtual

Reimplemented from CvStatModel.

§ write_params()

virtual void CvBoost::write_params ( CvFileStorage * fs ) const

protectedvirtual

Member Data Documentation

§ active_vars

CvMat* CvBoost::active_vars

protected

§ active_vars_abs

CvMat* CvBoost::active_vars_abs

protected

§ data

CvDTreeTrainData* CvBoost::data

protected

§ have_active_cat_vars

bool CvBoost::have_active_cat_vars

protected

§ have_subsample

bool CvBoost::have_subsample

protected

§ orig_response

CvMat* CvBoost::orig_response

protected

§ params

CvBoostParams CvBoost::params

protected

§ subsample_mask

CvMat* CvBoost::subsample_mask

protected

§ subtree_weights

CvMat* CvBoost::subtree_weights

protected

§ sum_response

CvMat* CvBoost::sum_response

protected

§ weak

CvSeq* CvBoost::weak

protected

§ weak_eval

CvMat* CvBoost::weak_eval

protected

§ weights

CvMat* CvBoost::weights

protected

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

ml/ml.hpp

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Member Enumeration Documentation

§ anonymous enum

§ anonymous enum

Constructor & Destructor Documentation

§ CvBoost() [1/3]

§ ~CvBoost()

§ CvBoost() [2/3]

§ CvBoost() [3/3]

Member Function Documentation

§ calc_error()

§ clear()

§ get_active_vars()

§ get_data()

§ get_params()

§ get_subtree_weights()

§ get_weak_predictors()

§ get_weak_response()

§ get_weights()

§ predict() [1/2]

§ predict() [2/2]

§ prune()

§ read()

§ read_params()

§ set_params()

§ train() [1/3]

§ train() [2/3]

§ train() [3/3]

§ trim_weights()

§ update_weights()

§ update_weights_impl()

§ write()

§ write_params()

Member Data Documentation

§ active_vars

§ active_vars_abs

§ data

§ have_active_cat_vars

§ have_subsample

§ orig_response

§ params

§ subsample_mask

§ subtree_weights

§ sum_response

§ weak

§ weak_eval

§ weights