Emgu.CV.ML Namespace |
| Class | Description | |
|---|---|---|
| ANN_MLP |
Neural network
| |
| Boost |
Boost Tree
| |
| DTrees |
Decision Trees
| |
| EM |
Expectation Maximization model
| |
| KNearest |
The KNearest classifier
| |
| LogisticRegression |
ML implements logistic regression, which is a probabilistic classification technique.
| |
| 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
| |
| SVMSGD |
Support Vector Machine
| |
| TrainData |
Train data
|
| Structure | Description | |
|---|---|---|
| MCvParamGrid |
Wrapped CvParamGrid structure used by SVM
|
| Interface | Description | |
|---|---|---|
| IStatModel |
Interface for statistical models in OpenCV ML.
|
| Enumeration | Description | |
|---|---|---|
| ANN_MLPAnnMlpActivationFunction |
Possible activation functions
| |
| ANN_MLPAnnMlpTrainMethod |
Training method for ANN_MLP
| |
| BoostType |
Boost Type
| |
| DTreesFlags |
Predict options
| |
| EMCovarianMatrixType |
The type of the mixture covariation matrices
| |
| KNearestTypes |
The type of KNearest search
| |
| LogisticRegressionRegularizationMethod |
Specifies the kind of regularization to be applied.
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| LogisticRegressionTrainType |
Specifies the kind of training method used.
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| SVMParamType |
The type of SVM parameters
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| SVMSvmKernelType |
SVM kernel type
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| SVMSvmType |
Type of SVM
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| SVMSGDMarginType |
Margin type
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| SVMSGDSvmsgdType |
SVMSGD type.
ASGD is often the preferable choice.
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