#include <ml.hpp>

Inheritance diagram for CvGBTrees:

Public Types
enum	{ SQUARED_LOSS =0, ABSOLUTE_LOSS, HUBER_LOSS =3, DEVIANCE_LOSS }

Public Member Functions
	CvGBTrees ()

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

virtual	~CvGBTrees ()

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, CvGBTreesParams params=CvGBTreesParams(), bool update=false)

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

virtual float	predict_serial (const CvMat sample, const CvMat missing=0, CvMat *weakResponses=0, CvSlice slice=CV_WHOLE_SEQ, int k=-1) const

virtual float	predict (const CvMat sample, const CvMat missing=0, CvMat *weakResponses=0, CvSlice slice=CV_WHOLE_SEQ, int k=-1) const

virtual void	clear ()

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

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

virtual void	read (CvFileStorage fs, CvFileNode node)

	CvGBTrees (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(), CvGBTreesParams params=CvGBTreesParams())

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(), CvGBTreesParams params=CvGBTreesParams(), bool update=false)

virtual float	predict (const cv::Mat &sample, const cv::Mat &missing=cv::Mat(), const cv::Range &slice=cv::Range::all(), int k=-1) 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
virtual void	find_gradient (const int k=0)

virtual void	change_values (CvDTree *tree, const int k=0)

virtual float	find_optimal_value (const CvMat *_Idx)

virtual void	do_subsample ()

void	leaves_get (CvDTreeNode *leaves, int &count, CvDTreeNode node)

CvDTreeNode **	GetLeaves (const CvDTree *dtree, int &len)

virtual bool	problem_type () const

virtual void	write_params (CvFileStorage *fs) const

virtual void	read_params (CvFileStorage fs, CvFileNode fnode)

int	get_len (const CvMat *mat) const

Protected Attributes
CvDTreeTrainData *	data

CvGBTreesParams	params

CvSeq **	weak

CvMat *	orig_response

CvMat *	sum_response

CvMat *	sum_response_tmp

CvMat *	sample_idx

CvMat *	subsample_train

CvMat *	subsample_test

CvMat *	missing

CvMat *	class_labels

cv::RNG *	rng

int	class_count

float	delta

float	base_value

Protected Attributes inherited from CvStatModel
const char *	default_model_name

Member Enumeration Documentation

anonymous enum

Enumerator
SQUARED_LOSS
ABSOLUTE_LOSS
HUBER_LOSS
DEVIANCE_LOSS

Constructor & Destructor Documentation

CvGBTrees::CvGBTrees ( )

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

virtual CvGBTrees::~CvGBTrees ( )

virtual

CvGBTrees::CvGBTrees	(	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()`,
		CvGBTreesParams	params = `CvGBTreesParams()`
	)

Member Function Documentation

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

virtual

virtual void CvGBTrees::change_values	(	CvDTree *	tree,
		const int	k = `0`
	)

protectedvirtual

virtual void CvGBTrees::clear ( )

virtual

Reimplemented from CvStatModel.

virtual void CvGBTrees::do_subsample ( )

protectedvirtual

virtual void CvGBTrees::find_gradient ( const int k = 0 )

protectedvirtual

virtual float CvGBTrees::find_optimal_value ( const CvMat * _Idx )

protectedvirtual

int CvGBTrees::get_len ( const CvMat * mat ) const

protected

CvDTreeNode** CvGBTrees::GetLeaves	(	const CvDTree *	dtree,
		int &	len
	)

protected

void CvGBTrees::leaves_get	(	CvDTreeNode **	leaves,
		int &	count,
		CvDTreeNode *	node
	)

protected

virtual float CvGBTrees::predict	(	const CvMat *	sample,
		const CvMat *	missing = `0`,
		CvMat *	weakResponses = `0`,
		CvSlice	slice = `CV_WHOLE_SEQ`,
		int	k = `-1`
	)		const

virtual

virtual float CvGBTrees::predict	(	const cv::Mat &	sample,
		const cv::Mat &	missing = `cv::Mat()`,
		const cv::Range &	slice = `cv::Range::all()`,
		int	k = `-1`
	)		const

virtual

virtual float CvGBTrees::predict_serial	(	const CvMat *	sample,
		const CvMat *	missing = `0`,
		CvMat *	weakResponses = `0`,
		CvSlice	slice = `CV_WHOLE_SEQ`,
		int	k = `-1`
	)		const

virtual

virtual bool CvGBTrees::problem_type ( ) const

protectedvirtual

virtual void CvGBTrees::read	(	CvFileStorage *	fs,
		CvFileNode *	node
	)

virtual

Reimplemented from CvStatModel.

virtual void CvGBTrees::read_params	(	CvFileStorage *	fs,
		CvFileNode *	fnode
	)

protectedvirtual

virtual bool CvGBTrees::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`,
		CvGBTreesParams	params = `CvGBTreesParams()`,
		bool	update = `false`
	)

virtual

virtual bool CvGBTrees::train	(	CvMLData *	data,
		CvGBTreesParams	params = `CvGBTreesParams()`,
		bool	update = `false`
	)

virtual

virtual bool CvGBTrees::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()`,
		CvGBTreesParams	params = `CvGBTreesParams()`,
		bool	update = `false`
	)

virtual

virtual void CvGBTrees::write	(	CvFileStorage *	fs,
		const char *	name
	)		const

virtual

Reimplemented from CvStatModel.

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

protectedvirtual

Member Data Documentation

float CvGBTrees::base_value

protected

int CvGBTrees::class_count

protected

CvMat* CvGBTrees::class_labels

protected

CvDTreeTrainData* CvGBTrees::data

protected

float CvGBTrees::delta

protected

CvMat* CvGBTrees::missing

protected

CvMat* CvGBTrees::orig_response

protected

CvGBTreesParams CvGBTrees::params

protected

cv::RNG* CvGBTrees::rng

protected

CvMat* CvGBTrees::sample_idx

protected

CvMat* CvGBTrees::subsample_test

protected

CvMat* CvGBTrees::subsample_train

protected

CvMat* CvGBTrees::sum_response

protected

CvMat* CvGBTrees::sum_response_tmp

protected

CvSeq** CvGBTrees::weak

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

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation