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. More... | |
void | randMVNormal (InputArray mean, InputArray cov, int nsamples, OutputArray samples) |
Generates sample from multivariate normal distribution. More... | |
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. More... | |