OpenCV  2.4.13.6
Open Source Computer Vision
ml/ml.hpp File Reference
#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_DEFAULT
)

§ cvRandMVNormal()

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