#include "opencv2/core/core.hpp"
#include <limits.h>
#include <map>
#include <string>
#include <iostream>

Classes
struct	CvVectors

class	CvStatModel

struct	CvParamGrid

class	CvNormalBayesClassifier

class	CvKNearest

struct	CvSVMParams

struct	CvSVMKernel

struct	CvSVMKernelRow

struct	CvSVMSolutionInfo

class	CvSVMSolver

struct	CvSVMDecisionFunc

class	CvSVM

class	cv::EM

struct	CvPair16u32s

struct	CvDTreeSplit

struct	CvDTreeNode

struct	CvDTreeParams

struct	CvDTreeTrainData

class	CvDTree

class	CvForestTree

struct	CvRTParams

class	CvRTrees

struct	CvERTreeTrainData

class	CvForestERTree

class	CvERTrees

struct	CvBoostParams

class	CvBoostTree

class	CvBoost

struct	CvGBTreesParams

class	CvGBTrees

struct	CvANN_MLP_TrainParams

class	CvANN_MLP

struct	CvTrainTestSplit

class	CvMLData

Namespaces
	cv

Macros
#define	CV_LOG2PI (1.8378770664093454835606594728112)

#define	CV_COL_SAMPLE 0

#define	CV_ROW_SAMPLE 1

#define	CV_IS_ROW_SAMPLE(flags) ((flags) & CV_ROW_SAMPLE)

#define	CV_VAR_NUMERICAL 0

#define	CV_VAR_ORDERED 0

#define	CV_VAR_CATEGORICAL 1

#define	CV_TYPE_NAME_ML_SVM "opencv-ml-svm"

#define	CV_TYPE_NAME_ML_KNN "opencv-ml-knn"

#define	CV_TYPE_NAME_ML_NBAYES "opencv-ml-bayesian"

#define	CV_TYPE_NAME_ML_EM "opencv-ml-em"

#define	CV_TYPE_NAME_ML_BOOSTING "opencv-ml-boost-tree"

#define	CV_TYPE_NAME_ML_TREE "opencv-ml-tree"

#define	CV_TYPE_NAME_ML_ANN_MLP "opencv-ml-ann-mlp"

#define	CV_TYPE_NAME_ML_CNN "opencv-ml-cnn"

#define	CV_TYPE_NAME_ML_RTREES "opencv-ml-random-trees"

#define	CV_TYPE_NAME_ML_ERTREES "opencv-ml-extremely-randomized-trees"

#define	CV_TYPE_NAME_ML_GBT "opencv-ml-gradient-boosting-trees"

#define	CV_TRAIN_ERROR 0

#define	CV_TEST_ERROR 1

#define	CV_DTREE_CAT_DIR(idx, subset) (2*((subset[(idx)>>5]&(1 << ((idx) & 31)))==0)-1)

#define	CV_TS_CONCENTRIC_SPHERES 0

#define	CV_COUNT 0

#define	CV_PORTION 1

Typedefs
typedef CvStatModel	cv::StatModel

typedef CvParamGrid	cv::ParamGrid

typedef CvNormalBayesClassifier	cv::NormalBayesClassifier

typedef CvKNearest	cv::KNearest

typedef CvSVMParams	cv::SVMParams

typedef CvSVMKernel	cv::SVMKernel

typedef CvSVMSolver	cv::SVMSolver

typedef CvSVM	cv::SVM

typedef CvDTreeParams	cv::DTreeParams

typedef CvMLData	cv::TrainData

typedef CvDTree	cv::DecisionTree

typedef CvForestTree	cv::ForestTree

typedef CvRTParams	cv::RandomTreeParams

typedef CvRTrees	cv::RandomTrees

typedef CvERTreeTrainData	cv::ERTreeTRainData

typedef CvForestERTree	cv::ERTree

typedef CvERTrees	cv::ERTrees

typedef CvBoostParams	cv::BoostParams

typedef CvBoostTree	cv::BoostTree

typedef CvBoost	cv::Boost

typedef CvANN_MLP_TrainParams	cv::ANN_MLP_TrainParams

typedef CvANN_MLP	cv::NeuralNet_MLP

typedef CvGBTreesParams	cv::GradientBoostingTreeParams

typedef CvGBTrees	cv::GradientBoostingTrees

Functions
void	cvRandMVNormal (CvMat mean, CvMat cov, CvMat sample, CvRNG rng CV_DEFAULT(0))

void	cvRandGaussMixture (CvMat means[], CvMat covs[], float weights[], int clsnum, CvMat sample, CvMat sampClasses CV_DEFAULT(0))

void	cvCreateTestSet (int type, CvMat samples, int num_samples, int num_features, CvMat responses, int num_classes,...)

bool	cv::initModule_ml (void)

Macro Definition Documentation

§ CV_COL_SAMPLE

#define CV_COL_SAMPLE 0

§ CV_COUNT

#define CV_COUNT 0

§ CV_DTREE_CAT_DIR

#define CV_DTREE_CAT_DIR	(	idx,
		subset
	)	(2*((subset[(idx)>>5]&(1 << ((idx) & 31)))==0)-1)

§ CV_IS_ROW_SAMPLE

#define CV_IS_ROW_SAMPLE ( flags ) ((flags) & CV_ROW_SAMPLE)

§ CV_LOG2PI

#define CV_LOG2PI (1.8378770664093454835606594728112)

§ CV_PORTION

#define CV_PORTION 1

§ CV_ROW_SAMPLE

#define CV_ROW_SAMPLE 1

§ CV_TEST_ERROR

#define CV_TEST_ERROR 1

§ CV_TRAIN_ERROR

#define CV_TRAIN_ERROR 0

§ CV_TS_CONCENTRIC_SPHERES

#define CV_TS_CONCENTRIC_SPHERES 0

§ CV_TYPE_NAME_ML_ANN_MLP

#define CV_TYPE_NAME_ML_ANN_MLP "opencv-ml-ann-mlp"

§ CV_TYPE_NAME_ML_BOOSTING

#define CV_TYPE_NAME_ML_BOOSTING "opencv-ml-boost-tree"

§ CV_TYPE_NAME_ML_CNN

#define CV_TYPE_NAME_ML_CNN "opencv-ml-cnn"

§ CV_TYPE_NAME_ML_EM

#define CV_TYPE_NAME_ML_EM "opencv-ml-em"

§ CV_TYPE_NAME_ML_ERTREES

#define CV_TYPE_NAME_ML_ERTREES "opencv-ml-extremely-randomized-trees"

§ CV_TYPE_NAME_ML_GBT

#define CV_TYPE_NAME_ML_GBT "opencv-ml-gradient-boosting-trees"

§ CV_TYPE_NAME_ML_KNN

#define CV_TYPE_NAME_ML_KNN "opencv-ml-knn"

§ CV_TYPE_NAME_ML_NBAYES

#define CV_TYPE_NAME_ML_NBAYES "opencv-ml-bayesian"

§ CV_TYPE_NAME_ML_RTREES

#define CV_TYPE_NAME_ML_RTREES "opencv-ml-random-trees"

§ CV_TYPE_NAME_ML_SVM

#define CV_TYPE_NAME_ML_SVM "opencv-ml-svm"

§ CV_TYPE_NAME_ML_TREE

#define CV_TYPE_NAME_ML_TREE "opencv-ml-tree"

§ CV_VAR_CATEGORICAL

#define CV_VAR_CATEGORICAL 1

§ CV_VAR_NUMERICAL

#define CV_VAR_NUMERICAL 0

§ CV_VAR_ORDERED

#define CV_VAR_ORDERED 0

Function Documentation

§ cvCreateTestSet()

void cvCreateTestSet	(	int	type,
		CvMat **	samples,
		int	num_samples,
		int	num_features,
		CvMat **	responses,
		int	num_classes,
			...
	)

§ cvRandGaussMixture()

void cvRandGaussMixture	(	CvMat *	means[],
		CvMat *	covs[],
		float	weights[],
		int	clsnum,
		CvMat *	sample,
		CvMat *sampClasses	CV_DEFAULT0
	)

§ cvRandMVNormal()

void cvRandMVNormal	(	CvMat *	mean,
		CvMat *	cov,
		CvMat *	sample,
		CvRNG *rng	CV_DEFAULT0
	)

Classes

Namespaces

Macros

Typedefs

Functions