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Train the ANN_MLP model with the specific paramters

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 static int CvANN_MLPTrain(
	IntPtr model,
	IntPtr trainData,
	IntPtr responses,
	IntPtr sampleWeights,
	IntPtr sampleIdx,
	ref MCvANN_MLP_TrainParams parameters,
	ANN_MLP_TRAINING_FLAG flags
)
Visual Basic
Public Shared Function CvANN_MLPTrain ( _
	model As IntPtr, _
	trainData As IntPtr, _
	responses As IntPtr, _
	sampleWeights As IntPtr, _
	sampleIdx As IntPtr, _
	ByRef parameters As MCvANN_MLP_TrainParams, _
	flags As ANN_MLP_TRAINING_FLAG _
) As Integer
Visual C++
public:
static int CvANN_MLPTrain(
	IntPtr model, 
	IntPtr trainData, 
	IntPtr responses, 
	IntPtr sampleWeights, 
	IntPtr sampleIdx, 
	MCvANN_MLP_TrainParams% parameters, 
	ANN_MLP_TRAINING_FLAG flags
)

Parameters

model
Type: System..::..IntPtr
The ANN_MLP model
trainData
Type: System..::..IntPtr
The training data. A 32-bit floating-point, single-channel matrix, one vector per row
responses
Type: System..::..IntPtr
A floating-point matrix of the corresponding output vectors, one vector per row.
sampleWeights
Type: System..::..IntPtr
(RPROP only) The optional floating-point vector of weights for each sample. Some samples may be more important than others for training, e.g. user may want to gain the weight of certain classes to find the right balance between hit-rate and false-alarm rate etc
sampleIdx
Type: System..::..IntPtr
Can be IntPtr.Zero if not needed. When specified, identifies samples of interest. It is a Matrix>int< of nx1
parameters
Type: Emgu.CV.ML.Structure..::..MCvANN_MLP_TrainParams%
The parameters for ANN_MLP
flags
Type: Emgu.CV.ML.MlEnum..::..ANN_MLP_TRAINING_FLAG
The traning flag

Return Value

The number of done iterations

See Also