RTrees Class 
Namespace: Emgu.CV.ML
The RTrees type exposes the following members.
Name  Description  

ActiveVarCount 
The size of the randomly selected subset of features at each tree node and that are used to find the best split(s)
 
CalculateVarImportance 
If true then variable importance will be calculated
 
CVFolds 
If CVFolds greater than 1 then algorithms prunes the built decision tree using Kfold
 
MaxCategories 
Cluster possible values of a categorical variable into K less than or equals maxCategories clusters to find a suboptimal split
 
MaxDepth 
The maximum possible depth of the tree
 
MinSampleCount 
If the number of samples in a node is less than this parameter then the node will not be split
 
Ptr 
Pointer to the unmanaged object
(Inherited from UnmanagedObject.)  
RegressionAccuracy 
Termination criteria for regression trees
 
TermCriteria 
The termination criteria that specifies when the training algorithm stops
 
TruncatePrunedTree 
If true then pruned branches are physically removed from the tree
 
Use1SERule 
If true then a pruning will be harsher
 
UseSurrogates 
If true then surrogate splits will be built

Name  Description  

Dispose 
The dispose function that implements IDisposable interface
(Inherited from DisposableObject.)  
DisposeObject 
Release the random tree and all memory associate with it
(Overrides DisposableObjectDisposeObject.)  
Equals  (Inherited from Object.)  
Finalize 
Destructor
(Inherited from DisposableObject.)  
GetHashCode  (Inherited from Object.)  
GetType  (Inherited from Object.)  
GetVotes 
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.
 
MemberwiseClone  (Inherited from Object.)  
ReleaseManagedResources 
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.)  
ToString  (Inherited from Object.) 
Name  Description  

_ptr 
A pointer to the unmanaged object
(Inherited from UnmanagedObject.) 
Name  Description  

Clear 
Clear the algorithm
(Defined by AlgorithmExtensions.)  
GetDefaultName 
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.)  
IsEmpty 
Returns true if the Algorithm is empty. e.g. in the very beginning or after unsuccessful read.
(Defined by AlgorithmExtensions.)  
Load 
Loads algorithm from the file
(Defined by AlgorithmExtensions.)  
LoadFromString 
Loads algorithm from a String
(Defined by AlgorithmExtensions.)  
Predict 
Predicts response(s) for the provided sample(s)
(Defined by StatModelExtensions.)  
Read 
Reads algorithm parameters from a file storage.
(Defined by AlgorithmExtensions.)  
Save 
Save the algorithm to file
(Defined by AlgorithmExtensions.)  
SaveToString 
Save the algorithm to a string
(Defined by AlgorithmExtensions.)  
Train(TrainData, Int32)  Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.)  
Train(IInputArray, DataLayoutType, IInputArray)  Overloaded.
Trains the statistical model.
(Defined by StatModelExtensions.)  
Write(FileStorage)  Overloaded.
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.)  
Write(FileStorage, String)  Overloaded.
Stores algorithm parameters in a file storage
(Defined by AlgorithmExtensions.) 