CvNormalBayesClassifier Class Reference

#include <ml.hpp>

Inheritance diagram for CvNormalBayesClassifier:

Public Member Functions
	CvNormalBayesClassifier ()
virtual	~CvNormalBayesClassifier ()
	CvNormalBayesClassifier (const CvMat *trainData, const CvMat *responses, const CvMat *varIdx=0, const CvMat *sampleIdx=0)
virtual bool	train (const CvMat *trainData, const CvMat *responses, const CvMat *varIdx=0, const CvMat *sampleIdx=0, bool update=false)
virtual float	predict (const CvMat *samples, CV_OUT CvMat *results=0) const
virtual void	clear ()
	CvNormalBayesClassifier (const cv::Mat &trainData, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat())
virtual bool	train (const cv::Mat &trainData, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat(), bool update=false)
virtual float	predict (const cv::Mat &samples, CV_OUT cv::Mat *results=0) const
virtual void	write (CvFileStorage *storage, const char *name) const
virtual void	read (CvFileStorage *storage, CvFileNode *node)
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 Attributes
int	var_count
int	var_all
CvMat *	var_idx
CvMat *	cls_labels
CvMat **	count
CvMat **	sum
CvMat **	productsum
CvMat **	avg
CvMat **	inv_eigen_values
CvMat **	cov_rotate_mats
CvMat *	c
Protected Attributes inherited from CvStatModel
const char *	default_model_name

Constructor & Destructor Documentation

CvNormalBayesClassifier() [1/3]

CvNormalBayesClassifier::CvNormalBayesClassifier

(

)

~CvNormalBayesClassifier()

virtual CvNormalBayesClassifier::~CvNormalBayesClassifier ( )

virtual

CvNormalBayesClassifier() [2/3]

CvNormalBayesClassifier::CvNormalBayesClassifier	(	const CvMat *	trainData,
		const CvMat *	responses,
		const CvMat *	varIdx = 0,
		const CvMat *	sampleIdx = 0
	)

CvNormalBayesClassifier() [3/3]

CvNormalBayesClassifier::CvNormalBayesClassifier	(	const cv::Mat &	trainData,
		const cv::Mat &	responses,
		const cv::Mat &	varIdx = cv::Mat(),
		const cv::Mat &	sampleIdx = cv::Mat()
	)

Member Function Documentation

clear()

virtual void CvNormalBayesClassifier::clear ( )

virtual

Reimplemented from CvStatModel.

predict() [1/2]

virtual float CvNormalBayesClassifier::predict ( const CvMat *  samples, CV_OUT CvMat *  results = 0  ) const

virtual

predict() [2/2]

virtual float CvNormalBayesClassifier::predict ( const cv::Mat &  samples, CV_OUT cv::Mat *  results = 0  ) const

virtual

read()

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

virtual

Reimplemented from CvStatModel.

train() [1/2]

virtual bool CvNormalBayesClassifier::train ( const CvMat *  trainData, const CvMat *  responses, const CvMat *  varIdx = 0, const CvMat *  sampleIdx = 0, bool  update = false  )

virtual

train() [2/2]

virtual bool CvNormalBayesClassifier::train ( const cv::Mat &  trainData, const cv::Mat &  responses, const cv::Mat &  varIdx = cv::Mat(), const cv::Mat &  sampleIdx = cv::Mat(), bool  update = false  )

virtual

write()

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

virtual

Reimplemented from CvStatModel.

Member Data Documentation

avg

CvMat** CvNormalBayesClassifier::avg

protected

c

CvMat* CvNormalBayesClassifier::c

protected

cls_labels

CvMat* CvNormalBayesClassifier::cls_labels

protected

count

CvMat** CvNormalBayesClassifier::count

protected

cov_rotate_mats

CvMat** CvNormalBayesClassifier::cov_rotate_mats

protected

inv_eigen_values

CvMat** CvNormalBayesClassifier::inv_eigen_values

protected

productsum

CvMat** CvNormalBayesClassifier::productsum

protected

sum

CvMat** CvNormalBayesClassifier::sum

protected

var_all

int CvNormalBayesClassifier::var_all

protected

var_count

int CvNormalBayesClassifier::var_count

protected

var_idx

CvMat* CvNormalBayesClassifier::var_idx

protected

---

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

• ml/ml.hpp