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: 2.2.1.1150 (2.2.1.1150)

Syntax

         
 C#  Visual Basic  Visual C++ 
public static float CvRTreesPredict(
	IntPtr model,
	IntPtr sample,
	IntPtr missingDataMask
)
Public Shared Function CvRTreesPredict ( _
	model As IntPtr, _
	sample As IntPtr, _
	missingDataMask As IntPtr _
) As Single
public:
static float CvRTreesPredict(
	IntPtr model, 
	IntPtr sample, 
	IntPtr missingDataMask
)

Parameters

model
IntPtr
The decision tree model
sample
IntPtr
The sample to be predicted
missingDataMask
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

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