| Package | Description |
|---|---|
| org.bytedeco.opencv.opencv_ml | |
| org.bytedeco.opencv.opencv_quality |
| Class and Description |
|---|
| AbstractStatModel |
| ANN_MLP
\brief Artificial Neural Networks - Multi-Layer Perceptrons.
|
| Boost
\brief Boosted tree classifier derived from DTrees
|
| DTrees
\brief The class represents a single decision tree or a collection of decision trees.
|
| DTrees.Node
\brief The class represents a decision tree node.
|
| DTrees.Split
\brief The class represents split in a decision tree.
|
| EM
\brief The class implements the Expectation Maximization algorithm.
|
| KNearest
\brief The class implements K-Nearest Neighbors model
|
| LogisticRegression
\brief Implements Logistic Regression classifier.
|
| NormalBayesClassifier
\brief Bayes classifier for normally distributed data.
|
| ParamGrid
\brief The structure represents the logarithmic grid range of statmodel parameters.
|
| RTrees
\brief The class implements the random forest predictor.
|
| StatModel
\brief Base class for statistical models in OpenCV ML.
|
| SVM
\brief Support Vector Machines.
|
| SVM.Kernel |
| SVMSGD
\brief Stochastic Gradient Descent SVM classifier
|
| TrainData
\brief Class encapsulating training data.
|
| Class and Description |
|---|
| SVM
\brief Support Vector Machines.
|
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