OpenCV  4.1.0
Open Source Computer Vision
Classes | Namespaces | Typedefs | Enumerations | Functions
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.