Emgu CV Library Documentation
Predict Method (sample, missingDataMask, rawMode)
NamespacesEmgu.CV.MLDTreePredict(Matrix<(Of <(Single>)>), Matrix<(Of <(Int32>)>), Boolean)

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The method takes the feature vector and the optional missing measurement mask on input, traverses the decision tree and returns the reached leaf node on output. The prediction result, either the class label or the estimated function value, may be retrieved as value field of the CvDTreeNode structure
Declaration Syntax
C#Visual BasicVisual C++
public MCvDTreeNode Predict(
	Matrix<float> sample,
	Matrix<int> missingDataMask,
	bool rawMode
)
Public Function Predict ( _
	sample As Matrix(Of Single), _
	missingDataMask As Matrix(Of Integer), _
	rawMode As Boolean _
) As MCvDTreeNode
public:
MCvDTreeNode Predict(
	Matrix<float>^ sample, 
	Matrix<int>^ missingDataMask, 
	bool rawMode
)
Parameters
sample (Matrix<(Of <(Single>)>))
The sample to be predicted
missingDataMask (Matrix<(Of <(Int32>)>))
Can be null 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)
rawMode (Boolean)
normally set to false that implies a regular input. If it is true, the method assumes that all the values of the discrete input variables have been already normalized to 0..num_of_categoriesi-1 ranges. (as the decision tree uses such normalized representation internally). It is useful for faster prediction with tree ensembles. For ordered input variables the flag is not used.
Return Value
Pointer to the reached leaf node on output. The prediction result, either the class label or the estimated function value, may be retrieved as value field of the CvDTreeNode structure

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