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.
- SVM
Support Vector Machines
- StatModel
Base class for statistical models in ML
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
- SVM.KernelTypes
SVM kernel type
- SVM.ParamTypes
SVM params type
- SVM.Types
SVM type
- SampleTypes
Sample types
- StatModel.Flags
Predict options