ResilientBackpropagation Class 
Namespace: Accord.Math.Optimization
public class ResilientBackpropagation : BaseGradientOptimizationMethod, IGradientOptimizationMethod, IOptimizationMethod, IOptimizationMethod<double[], double>, IGradientOptimizationMethod<double[], double>, IFunctionOptimizationMethod<double[], double>
The ResilientBackpropagation type exposes the following members.
Name  Description  

ResilientBackpropagation(Int32) 
Creates a new ResilientBackpropagation function optimizer.
 
ResilientBackpropagation(NonlinearObjectiveFunction) 
Creates a new ResilientBackpropagation function optimizer.
 
ResilientBackpropagation(Int32, FuncDouble, Double, FuncDouble, Double) 
Creates a new ResilientBackpropagation function optimizer.

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 loglikelihood
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 1e6.
 
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.) 
Name  Description  

Equals  Determines whether the specified object is equal to the current object. (Inherited from Object.)  
Finalize  Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)  
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetType  Gets the Type of the current instance. (Inherited from Object.)  
Maximize 
Finds the maximum value of a function. The solution vector
will be made available at the Solution property.
(Inherited from BaseGradientOptimizationMethod.)  
Maximize(Double) 
Finds the maximum value of a function. The solution vector
will be made available at the Solution property.
(Inherited from BaseOptimizationMethod.)  
MemberwiseClone  Creates a shallow copy of the current Object. (Inherited from Object.)  
Minimize 
Finds the minimum value of a function. The solution vector
will be made available at the Solution property.
(Inherited from BaseGradientOptimizationMethod.)  
Minimize(Double) 
Finds the minimum value of a function. The solution vector
will be made available at the Solution property.
(Inherited from BaseOptimizationMethod.)  
OnNumberOfVariablesChanged 
Called when the NumberOfVariables property has changed.
(Overrides BaseOptimizationMethodOnNumberOfVariablesChanged(Int32).)  
OnProgressChanged 
Raises the [E:ProgressChanged] event.
 
Optimize 
Implements the actual optimization algorithm. This
method should try to minimize the objective function.
(Overrides BaseOptimizationMethodOptimize.)  
Reset 
Resets the current update steps using the given learning rate.
 
ToString  Returns a string that represents the current object. (Inherited from Object.) 
Name  Description  

ProgressChanged 
Occurs when the current learning progress has changed.

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.) 