Namespace OpenCvSharp.ML

Classes

ANN_MLP

Artificial Neural Networks - Multi-Layer Perceptrons.

Boost

Boosted tree classifier derived from DTrees

DTrees

Decision tree

KNearest

K nearest neighbors classifier

LogisticRegression

Implements Logistic Regression classifier.

NormalBayesClassifier

Bayes classifier for normally distributed data

RTrees

The class implements the random forest predictor.

StatModel

Base class for statistical models in ML

SVM

Support Vector Machines

TrainData

Structs

DTrees.Node

The class represents a decision tree node.

DTrees.Split

The class represents split in a decision tree.

ParamGrid

The structure represents the logarithmic grid range of statmodel parameters.

Enums

ANN_MLP.ActivationFunctions

possible activation functions

ANN_MLP.TrainFlags

Train options

ANN_MLP.TrainingMethods

Available training methods

Boost.Types

Boosting type. Gentle AdaBoost and Real AdaBoost are often the preferable choices.

KNearest.Types

Implementations of KNearest algorithm

LogisticRegression.Methods

Training methods

LogisticRegression.RegKinds

Regularization kinds

SampleTypes

Sample types

StatModel.Flags

Predict options

SVM.KernelTypes

SVM kernel type

SVM.ParamTypes

SVM params type

SVM.Types

SVM type