|  | OpenCV
    3.4.11
    Open Source Computer Vision | 
#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::ANN_MLP_ANNEAL | 
| 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 | |
| cv | |
| cv::ml | |
| 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.  More... | |
| void | cv::ml::randMVNormal (InputArray mean, InputArray cov, int nsamples, OutputArray samples) | 
| Generates sample from multivariate normal distribution.  More... | |
| 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.  More... | |
 1.8.13
 1.8.13