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The method takes the feature vector and the optional missing measurement mask on input, traverses the random tree and returns the cumulative result from all the trees in the forest (the class that receives the majority of voices, or the mean of the regression function estimates)

Namespace: Emgu.CV.ML
Assembly: Emgu.CV.ML (in Emgu.CV.ML.dll) Version: 2.4.10.1935 (2.4.10.1935)

Syntax

C#
public static float CvRTreesPredict(
	IntPtr model,
	IntPtr sample,
	IntPtr missingDataMask
)
Visual Basic
Public Shared Function CvRTreesPredict ( 
	model As IntPtr,
	sample As IntPtr,
	missingDataMask As IntPtr
) As Single
Visual C++
public:
static float CvRTreesPredict(
	IntPtr model, 
	IntPtr sample, 
	IntPtr missingDataMask
)
F#
static member CvRTreesPredict : 
        model : IntPtr * 
        sample : IntPtr * 
        missingDataMask : IntPtr -> float32 

Parameters

model
Type: System..::..IntPtr
The decision tree model
sample
Type: System..::..IntPtr
The sample to be predicted
missingDataMask
Type: System..::..IntPtr
Can be IntPtr.Zero if not needed. When specified, it is an 8-bit matrix of the same size as trainData, is used to mark the missed values (non-zero elements of the mask)

Return Value

Type: Single
The cumulative result from all the trees in the forest (the class that receives the majority of voices, or the mean of the regression function estimates)

See Also