Emgu.CV.ML Namespace |
Wrapper of OpenCV's Machine Learning Library
Classes| Class | Description | |
|---|---|---|
 | ANN_MLP |
Neural network
|
| ANN_MLPAnnMlpActivationFunction |
Possible activation functions
|
| ANN_MLPAnnMlpTrainMethod |
Training method for ANN_MLP
|
| Boost |
Boost Tree
|
| BoostType |
Boost Type
|
| DTrees |
Decision Trees
|
| DTreesFlags |
Predict options
|
| EM |
Expectation Maximization model
|
| EMCovarianMatrixType |
The type of the mixture covariation matrices
|
| KNearest |
The KNearest classifier
|
| KNearestTypes |
The type of KNearest search
|
| LogisticRegression |
ML implements logistic regression, which is a probabilistic classification technique.
|
| LogisticRegressionRegularizationMethod |
Specifies the kind of regularization to be applied.
|
| LogisticRegressionTrainType |
Specifies the kind of training method used.
|
| MCvParamGrid |
Wrapped CvParamGrid structure used by SVM
|
| MlInvoke |
This class contains functions to call into machine learning library
|
| NormalBayesClassifier |
A Normal Bayes Classifier
|
| RTrees |
Random trees
|
| StatModelExtensions |
A statistic model
|
| SVM |
Support Vector Machine
|
| SVMParamType |
The type of SVM parameters
|
| SVMSvmKernelType |
SVM kernel type
|
| SVMSvmType |
Type of SVM
|
| SVMSGD |
Support Vector Machine
|
| SVMSGDMarginType |
Margin type
|
| SVMSGDSvmsgdType |
SVMSGD type.
ASGD is often the preferable choice.
|
| TrainData |
Train data
|
Interfaces| Interface | Description | |
|---|---|---|
 | IStatModel |
Interface for statistical models in OpenCV ML.
|