cv::ml Namespace Reference

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

Typedefs
typedef ANN_MLP	ANN_MLP_ANNEAL

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

Functions
void	createConcentricSpheresTestSet (int nsamples, int nfeatures, int nclasses, OutputArray samples, OutputArray responses)
	Creates test set.
void	randMVNormal (InputArray mean, InputArray cov, int nsamples, OutputArray samples)
	Generates sample from multivariate normal distribution.
template<class SimulatedAnnealingSolverSystem >
int	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.