Emgu CV Library Documentation
CvANN_MLPTrain Method (model, trainData, responses, sampleWeights, sampleIdx, parameters, flags)
NamespacesEmgu.CV.MLMlInvokeCvANN_MLPTrain(IntPtr, IntPtr, IntPtr, IntPtr, IntPtr, MCvANN_MLP_TrainParams, ANN_MLP_TRAINING_FLAG)

www.emgu.com/wiki
Train the ANN_MLP model with the specific paramters
Declaration Syntax
C#Visual BasicVisual 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
)
Public Shared Function CvANN_MLPTrain ( _
	model As IntPtr, _
	trainData As IntPtr, _
	responses As IntPtr, _
	sampleWeights As IntPtr, _
	sampleIdx As IntPtr, _
	parameters As MCvANN_MLP_TrainParams, _
	flags As ANN_MLP_TRAINING_FLAG _
) As Integer
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 (IntPtr)
The ANN_MLP model
trainData (IntPtr)
The training data. A 32-bit floating-point, single-channel matrix, one vector per row
responses (IntPtr)
A floating-point matrix of the corresponding output vectors, one vector per row.
sampleWeights (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 (IntPtr)
Can be IntPtr.Zero if not needed. When specified, identifies samples of interest. It is a Matrix>int< of nx1
parameters (MCvANN_MLP_TrainParams)
The parameters for ANN_MLP
flags (ANN_MLP_TRAINING_FLAG)
The traning flag
Return Value
The number of done iterations

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