Train the random tree using the specific traning data

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 bool CvRTreesTrain(
	IntPtr model,
	IntPtr trainData,
	DATA_LAYOUT_TYPE tFlag,
	IntPtr responses,
	IntPtr varIdx,
	IntPtr sampleIdx,
	IntPtr varType,
	IntPtr missingMask,
	MCvRTParams param
)
Public Shared Function CvRTreesTrain ( _
	model As IntPtr, _
	trainData As IntPtr, _
	tFlag As DATA_LAYOUT_TYPE, _
	responses As IntPtr, _
	varIdx As IntPtr, _
	sampleIdx As IntPtr, _
	varType As IntPtr, _
	missingMask As IntPtr, _
	param As MCvRTParams _
) As Boolean
public:
static bool CvRTreesTrain(
	IntPtr model, 
	IntPtr trainData, 
	DATA_LAYOUT_TYPE tFlag, 
	IntPtr responses, 
	IntPtr varIdx, 
	IntPtr sampleIdx, 
	IntPtr varType, 
	IntPtr missingMask, 
	MCvRTParams param
)

Parameters

model
IntPtr
The Random Tree model
trainData
IntPtr
The training data. A 32-bit floating-point, single-channel matrix, one vector per row
tFlag
DATA_LAYOUT_TYPE
The data layout type of the train data
responses
IntPtr
A floating-point matrix of the corresponding output vectors, one vector per row.
varIdx
IntPtr
Can be IntPtr.Zero if not needed. When specified, identifies variables (features) of interest. It is a Matrix<int> of nx1
sampleIdx
IntPtr
Can be IntPtr.Zero if not needed. When specified, identifies samples of interest. It is a Matrix<int> of nx1
varType
IntPtr
The types of input variables
missingMask
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)
param
MCvRTParams
The parameters for training the random tree

Return Value

[Missing <returns> documentation for "M:Emgu.CV.ML.MlInvoke.CvRTreesTrain(System.IntPtr,System.IntPtr,Emgu.CV.ML.MlEnum.DATA_LAYOUT_TYPE,System.IntPtr,System.IntPtr,System.IntPtr,System.IntPtr,System.IntPtr,Emgu.CV.ML.Structure.MCvRTParams)"]

See Also