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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)

Declaration Syntax
Public Shared Function CvRTreesPredict ( _
model As IntPtr, _
sample As IntPtr, _
missingDataMask As IntPtr _
) As Single

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)
Assembly:
Emgu.CV.ML (Module: Emgu.CV.ML) Version: 1.0.0.0 (1.0.0.0)