CvANN_MLP_TrainParams Class OpenCvSharp Class Library
Parameters of MLP training algorithm
Inheritance Hierarchy

SystemObject
  OpenCvSharp.CPlusPlusCvANN_MLP_TrainParams

Namespace:  OpenCvSharp.CPlusPlus
Assembly:  OpenCvSharp.CPlusPlus (in OpenCvSharp.CPlusPlus.dll) Version: 1.0.0.0 (1.0.0.0)
Syntax

public class CvANN_MLP_TrainParams

The CvANN_MLP_TrainParams type exposes the following members.

Constructors

  NameDescription
Public methodCvANN_MLP_TrainParams
Default constructor
Public methodCvANN_MLP_TrainParams(TermCriteria, MLPTrainingMethod, Double, Double)
Training constructor
Top
Properties

  NameDescription
Public propertyBpDwScale
(Backpropagation only): The coefficient to multiply the computed weight gradient by. The recommended value is about 0.1. The parameter can be set via param1 of the constructor.
Public propertyBpMomentScale
(Backpropagation only): The coefficient to multiply the difference between weights on the 2 previous iterations. This parameter provides some inertia to smooth the random fluctuations of the weights. It can vary from 0 (the feature is disabled) to 1 and beyond. The value 0.1 or so is good enough. The parameter can be set via param2 of the constructor.
Public propertyRpDw0
(RPROP only): Initial magnitude of the weight delta. The default value is 0.1. This parameter can be set via param1 of the constructor.
Public propertyRpDwMax
(RPROP only): The maximum value of the weight delta. It must be >1, the default value is 50. The parameter can only be changed explicitly by modifying the structure member.
Public propertyRpDwMin
(RPROP only): The minimum value of the weight delta. It must be >0, the default value is FLT_EPSILON. The parameter can be set via param2 of the constructor.
Public propertyRpDwMinus
(RPROP only): The decrease factor for the weight delta. It must be <1, default value is 0.5 that should work well in most cases, according to the algorithm's author. The parameter can only be changed explicitly by modifying the structure member.
Public propertyRpDwPlus
(RPROP only): The increase factor for the weight delta. It must be >1, default value is 1.2 that should work well in most cases, according to the algorithm's author. The parameter can only be changed explicitly by modifying the structure member.
Public propertyTermCrit
The termination criteria for the training algorithm. It identifies how many iterations is done by the algorithm (for sequential backpropagation algorithm the number is multiplied by the size of the training set) and how much the weights could change between the iterations to make the algorithm continue.
Public propertyTrainMethod
The training algorithm to use
Top
Methods

  NameDescription
Public methodEquals (Inherited from Object.)
Protected methodFinalize (Inherited from Object.)
Public methodGetHashCode (Inherited from Object.)
Public methodGetType (Inherited from Object.)
Protected methodMemberwiseClone (Inherited from Object.)
Public methodToString (Inherited from Object.)
Top
See Also

Reference