opencv2/ml.hpp

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

Include dependency graph for ml.hpp:

This graph shows which files directly or indirectly include ml.hpp:

Classes

class cv::ml::ANN_MLP

Artificial Neural Networks - Multi-Layer Perceptrons.

class cv::ml::Boost

Boosted tree classifier derived from DTrees.

class cv::ml::DTrees

The class represents a single decision tree or a collection of decision trees.

class cv::ml::EM

The class implements the Expectation Maximization algorithm.

class cv::ml::SVM::Kernel

class cv::ml::KNearest

The class implements K-Nearest Neighbors model.

class cv::ml::LogisticRegression

Implements Logistic Regression classifier.

class cv::ml::DTrees::Node

The class represents a decision tree node.

class cv::ml::NormalBayesClassifier

Bayes classifier for normally distributed data.

class cv::ml::ParamGrid

The structure represents the logarithmic grid range of statmodel parameters.

class cv::ml::RTrees

The class implements the random forest predictor.

struct cv::ml::SimulatedAnnealingSolverSystem

This class declares example interface for system state used in simulated annealing optimization algorithm.

class cv::ml::DTrees::Split

The class represents split in a decision tree.

class cv::ml::StatModel

Base class for statistical models in OpenCV ML.

class cv::ml::SVM

Support Vector Machines.

class cv::ml::SVMSGD

Stochastic Gradient Descent SVM classifier.

class cv::ml::TrainData

Class encapsulating training data.

Namespaces

namespace cv

namespace cv::ml

Enumerations

enum cv::ml::ErrorTypes {
TEST_ERROR = 0,
TRAIN_ERROR = 1
}

Error types More…

enum cv::ml::SampleTypes {
ROW_SAMPLE = 0,
COL_SAMPLE = 1
}

Sample types. More…

enum cv::ml::VariableTypes {
VAR_NUMERICAL =0,
VAR_ORDERED =0,
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.

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.