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RTrees Class
Random trees
Inheritance Hierarchy

Namespace:  Emgu.CV.ML
Assembly:  Emgu.CV.World (in Emgu.CV.World.dll) Version: (
public class RTrees : UnmanagedObject, IStatModel, 

The RTrees type exposes the following members.

Public methodRTrees
Create a random tree
Public propertyActiveVarCount
The size of the randomly selected subset of features at each tree node and that are used to find the best split(s)
Public propertyCalculateVarImportance
If true then variable importance will be calculated
Public propertyCVFolds
If CVFolds greater than 1 then algorithms prunes the built decision tree using K-fold
Public propertyMaxCategories
Cluster possible values of a categorical variable into K less than or equals maxCategories clusters to find a suboptimal split
Public propertyMaxDepth
The maximum possible depth of the tree
Public propertyMinSampleCount
If the number of samples in a node is less than this parameter then the node will not be split
Public propertyPtr
Pointer to the unmanaged object
(Inherited from UnmanagedObject.)
Public propertyRegressionAccuracy
Termination criteria for regression trees
Public propertyTermCriteria
The termination criteria that specifies when the training algorithm stops
Public propertyTruncatePrunedTree
If true then pruned branches are physically removed from the tree
Public propertyUse1SERule
If true then a pruning will be harsher
Public propertyUseSurrogates
If true then surrogate splits will be built
Public methodDispose
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.)
Protected methodDisposeObject
Release the random tree and all memory associate with it
(Overrides DisposableObjectDisposeObject.)
Public methodEquals (Inherited from Object.)
Protected methodFinalize
(Inherited from DisposableObject.)
Public methodGetHashCode (Inherited from Object.)
Public methodGetType (Inherited from Object.)
Public methodGetVotes
Returns the result of each individual tree in the forest. In case the model is a regression problem, the method will return each of the trees' results for each of the sample cases.If the model is a classifier, it will return a Mat with samples + 1 rows, where the first row gives the class number and the following rows return the votes each class had for each sample.
Protected methodMemberwiseClone (Inherited from Object.)
Protected methodReleaseManagedResources
Release the managed resources. This function will be called during the disposal of the current object. override ride this function if you need to call the Dispose() function on any managed IDisposable object created by the current object
(Inherited from DisposableObject.)
Public methodToString (Inherited from Object.)
Protected field_ptr
A pointer to the unmanaged object
(Inherited from UnmanagedObject.)
Extension Methods
Public Extension MethodClear
Clear the algorithm
(Defined by AlgorithmExtensions.)
Public Extension MethodGetDefaultName
Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.
(Defined by AlgorithmExtensions.)
Public Extension MethodIsEmpty
Returns true if the Algorithm is empty. e.g. in the very beginning or after unsuccessful read.
(Defined by AlgorithmExtensions.)
Public Extension MethodLoad
Loads algorithm from the file
(Defined by AlgorithmExtensions.)
Public Extension MethodLoadFromString
Loads algorithm from a String
(Defined by AlgorithmExtensions.)
Public Extension MethodPredict
Predicts response(s) for the provided sample(s)
(Defined by StatModelExtensions.)
Public Extension MethodRead
Reads algorithm parameters from a file storage.
(Defined by AlgorithmExtensions.)
Public Extension MethodSave
Save the algorithm to file
(Defined by AlgorithmExtensions.)
Public Extension MethodSaveToString
Save the algorithm to a string
(Defined by AlgorithmExtensions.)
Public Extension MethodTrain(TrainData, Int32)Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.)
Public Extension MethodTrain(IInputArray, DataLayoutType, IInputArray)Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.)
Public Extension MethodWrite(FileStorage)Overloaded.
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.)
Public Extension MethodWrite(FileStorage, String)Overloaded.
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.)
See Also