CvBoost Class Reference

#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
virtual float	calc_error (CvMLData _data, int type, std::vector< float > resp=0)
virtual CV_WRAP void	clear ()
CV_WRAP	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())
	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())
CV_WRAP	CvBoost ()
virtual const CvMat *	get_active_vars (bool absolute_idx=true)
const CvDTreeTrainData *	get_data () const
const CvBoostParams &	get_params () const
CvMat *	get_subtree_weights ()
CvSeq *	get_weak_predictors ()
CvMat *	get_weak_response ()
CvMat *	get_weights ()
virtual CV_WRAP 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	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 CV_WRAP void	prune (CvSlice slice)
virtual void	read (CvFileStorage storage, CvFileNode node)
virtual CV_WRAP 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 bool	train (CvMLData *data, CvBoostParams params=CvBoostParams(), bool update=false)
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 void	write (CvFileStorage storage, const char name) const
virtual	~CvBoost ()
Protected Member Functions
virtual void	read_params (CvFileStorage fs, CvFileNode node)
virtual bool	set_params (const CvBoostParams &params)
virtual void	trim_weights ()
virtual void	update_weights (CvBoostTree *tree)
virtual void	write_params (CvFileStorage *fs) const
Protected Attributes
CvMat *	active_vars
CvMat *	active_vars_abs
CvDTreeTrainData *	data
bool	have_active_cat_vars
bool	have_subsample
CvMat *	orig_response
CvBoostParams	params
CvMat *	subsample_mask
CvMat *	subtree_weights
CvMat *	sum_response
CvSeq *	weak
CvMat *	weak_eval
CvMat *	weights

Member Enumeration Documentation

anonymous enum

Enumerator:

DISCRETE
REAL
LOGIT
GENTLE

anonymous enum

Enumerator:

DEFAULT
GINI
MISCLASS
SQERR

Constructor & Destructor Documentation

CV_WRAP CvBoost::CvBoost ( )

virtual CvBoost::~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()`
	)

CV_WRAP 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

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

virtual CV_WRAP void CvBoost::clear ( ) [virtual]

Reimplemented from CvStatModel.

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

const CvDTreeTrainData* CvBoost::get_data ( ) const

const CvBoostParams& CvBoost::get_params ( ) const

CvMat* CvBoost::get_subtree_weights ( )

CvSeq* CvBoost::get_weak_predictors ( )

CvMat* CvBoost::get_weak_response ( )

CvMat* CvBoost::get_weights ( )

virtual CV_WRAP 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]`

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]`

virtual CV_WRAP void CvBoost::prune ( CvSlice slice ) [virtual]

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

Reimplemented from CvStatModel.

virtual void CvBoost::read_params	(	CvFileStorage *	fs,
		CvFileNode *	node
	)			`[protected, virtual]`

virtual bool CvBoost::set_params ( const CvBoostParams & params ) [protected, virtual]

virtual CV_WRAP 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]`

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

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]`