Train the ANN_MLP model with the specific paramters
Namespace: Emgu.CV.MLAssembly: 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 int CvANN_MLPTrain( IntPtr model, IntPtr trainData, IntPtr responses, IntPtr sampleWeights, IntPtr sampleIdx, ref 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, _ ByRef 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