http://www.emgu.com
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

Namespace: Emgu.CV.ML
Assembly: Emgu.CV.ML (in Emgu.CV.ML.dll) Version: 2.4.0.1717 (2.4.0.1717)

Syntax

C#
public MCvDTreeNode Predict(
	Matrix<float> sample,
	Matrix<byte> missingDataMask,
	bool rawMode
)
Visual Basic
Public Function Predict ( _
	sample As Matrix(Of Single), _
	missingDataMask As Matrix(Of Byte), _
	rawMode As Boolean _
) As MCvDTreeNode
Visual C++
public:
MCvDTreeNode Predict(
	Matrix<float>^ sample, 
	Matrix<unsigned char>^ missingDataMask, 
	bool rawMode
)

Parameters

sample
Type: Emgu.CV..::..Matrix<(Of <(<'Single>)>)>
The sample to be predicted
missingDataMask
Type: Emgu.CV..::..Matrix<(Of <(<'Byte>)>)>
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
Type: System..::..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

See Also