ml.hpp File Reference

#include "opencv2/core.hpp"
#include <float.h>
#include <map>
#include <iostream>
#include <opencv2/ml/ml.inl.hpp>

Classes
class	cv::ml::ANN_MLP
	Artificial Neural Networks - Multi-Layer Perceptrons. More...
class	cv::ml::Boost
	Boosted tree classifier derived from DTrees. More...
class	cv::ml::DTrees
	The class represents a single decision tree or a collection of decision trees. More...
class	cv::ml::EM
	The class implements the Expectation Maximization algorithm. More...
class	cv::ml::SVM::Kernel
class	cv::ml::KNearest
	The class implements K-Nearest Neighbors model. More...
class	cv::ml::LogisticRegression
	Implements Logistic Regression classifier. More...
class	cv::ml::DTrees::Node
	The class represents a decision tree node. More...
class	cv::ml::NormalBayesClassifier
	Bayes classifier for normally distributed data. More...
class	cv::ml::ParamGrid
	The structure represents the logarithmic grid range of statmodel parameters. More...
class	cv::ml::RTrees
	The class implements the random forest predictor. More...
struct	cv::ml::SimulatedAnnealingSolverSystem
	This class declares example interface for system state used in simulated annealing optimization algorithm. More...
class	cv::ml::DTrees::Split
	The class represents split in a decision tree. More...
class	cv::ml::StatModel
	Base class for statistical models in OpenCV ML. More...
class	cv::ml::SVM
	Support Vector Machines. More...
class	cv::ml::SVMSGD
	Stochastic Gradient Descent SVM classifier. More...
class	cv::ml::TrainData
	Class encapsulating training data. More...

Namespaces
namespace	cv
	"black box" representation of the file storage associated with a file on disk.
namespace	cv::ml

Typedefs
typedef ANN_MLP	cv::ml::ANN_MLP_ANNEAL

Enumerations
enum	cv::ml::ErrorTypes {   cv::ml::TEST_ERROR = 0,   cv::ml::TRAIN_ERROR = 1 }
	Error types More...
enum	cv::ml::SampleTypes {   cv::ml::ROW_SAMPLE = 0,   cv::ml::COL_SAMPLE = 1 }
	Sample types. More...
enum	cv::ml::VariableTypes {   cv::ml::VAR_NUMERICAL =0,   cv::ml::VAR_ORDERED =0,   cv::ml::VAR_CATEGORICAL =1 }
	Variable types. More...

Functions
void	cv::ml::createConcentricSpheresTestSet (int nsamples, int nfeatures, int nclasses, OutputArray samples, OutputArray responses)
	Creates test set.
void	cv::ml::randMVNormal (InputArray mean, InputArray cov, int nsamples, OutputArray samples)
	Generates sample from multivariate normal distribution.
template<class SimulatedAnnealingSolverSystem >
int	cv::ml::simulatedAnnealingSolver (SimulatedAnnealingSolverSystem &solverSystem, double initialTemperature, double finalTemperature, double coolingRatio, size_t iterationsPerStep, double *lastTemperature=NULL, cv::RNG &rngEnergy=cv::theRNG())
	The class implements simulated annealing for optimization.