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Showing content from http://accord-framework.net/docs/html/T_Accord_Math_Optimization_ResilientBackpropagation.htm below:

ResilientBackpropagation Class

Resilient Backpropagation method for unconstrained optimization.

Inheritance Hierarchy Namespace:  Accord.Math.Optimization
Assembly:

Accord.Math (in Accord.Math.dll) Version: 3.8.0

Syntax
public class ResilientBackpropagation : BaseGradientOptimizationMethod, 
	IGradientOptimizationMethod, IOptimizationMethod, IOptimizationMethod<double[], double>, 
	IGradientOptimizationMethod<double[], double>, IFunctionOptimizationMethod<double[], double>
Public Class ResilientBackpropagation
	Inherits BaseGradientOptimizationMethod
	Implements IGradientOptimizationMethod, IOptimizationMethod, IOptimizationMethod(Of Double(), Double), 
	IGradientOptimizationMethod(Of Double(), Double), IFunctionOptimizationMethod(Of Double(), Double)
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The ResilientBackpropagation type exposes the following members.

Constructors Properties   Name Description DecreaseFactor

Gets the decrease parameter, also referred as eta minus. Default is 0.5.

Function

Gets or sets the function to be optimized.

(Inherited from BaseOptimizationMethod.) Gradient

Gets or sets a function returning the gradient vector of the function to be optimized for a given value of its free parameters.

(Inherited from BaseGradientOptimizationMethod.) IncreaseFactor

Gets the increase parameter, also referred as eta plus. Default is 1.2.

Iterations

Gets or sets the maximum number of iterations performed by the learning algorithm.

NumberOfVariables

Gets the number of variables (free parameters) in the optimization problem.

(Inherited from BaseOptimizationMethod.) Solution

Gets the current solution found, the values of the parameters which optimizes the function.

(Inherited from BaseOptimizationMethod.) Token

Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running.

(Inherited from BaseOptimizationMethod.) Tolerance

Gets or sets the maximum change in the average log-likelihood after an iteration of the algorithm used to detect convergence.

UpdateLowerBound

Gets or sets the minimum possible update step, also referred as delta max. Default is 1e-6.

UpdateUpperBound

Gets or sets the maximum possible update step, also referred as delta min. Default is 50.

Value

Gets the output of the function at the current

Solution

.

(Inherited from BaseOptimizationMethod.) Top Methods Events   Name Description ProgressChanged

Occurs when the current learning progress has changed.

Top Extension Methods   Name Description HasMethod

Checks whether an object implements a method with the given name.

(Defined by ExtensionMethods.) IsEqual

Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.

(Defined by Matrix.) To(Type) Overloaded.

Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.

(Defined by ExtensionMethods.) ToT Overloaded.

Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.

(Defined by ExtensionMethods.) Top See Also

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