OpenCV
4.0.0
Open Source Computer Vision
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#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 | |
cv | |
"black box" representation of the file storage associated with a file on disk. | |
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. 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... | |