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SymbolicRegressionFitness Class
Fitness function for symbolic regression (function approximation) problem
Inheritance Hierarchy
SystemObject
  Accord.GeneticSymbolicRegressionFitness

Namespace:  Accord.Genetic
Assembly:  Accord.Genetic (in Accord.Genetic.dll) Version: 3.8.0
Syntax
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public class SymbolicRegressionFitness : IFitnessFunction
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The SymbolicRegressionFitness type exposes the following members.

Constructors
  NameDescription
Public methodSymbolicRegressionFitness
Initializes a new instance of the SymbolicRegressionFitness class.
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Methods
  NameDescription
Public methodEquals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Public methodEvaluate
Evaluates chromosome.
Protected methodFinalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Public methodGetHashCode
Serves as the default hash function.
(Inherited from Object.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Protected methodMemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
Public methodTranslate
Translates genotype to phenotype .
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Extension Methods
  NameDescription
Public Extension MethodHasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
Public Extension MethodIsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)
Public Extension MethodTo(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.)
Public Extension MethodToTOverloaded.
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.)
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Remarks

The fitness function calculates fitness value of GP and GEP chromosomes with the aim of solving symbolic regression problem. The fitness function's value is computed as:

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100.0 / ( error + 1 )
where error equals to the sum of absolute differences between function values (computed using the function encoded by chromosome) and input values (function to be approximated).

Sample usage:

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// constants
double[] constants = new double[5] { 1, 2, 3, 5, 7 };
// function to be approximated
double[,] data = new double[5, 2] {
    {1, 1}, {2, 3}, {3, 6}, {4, 10}, {5, 15} };
// create population
Population population = new Population( 100,
    new GPTreeChromosome( new SimpleGeneFunction( 1 + constants.Length ) ),
    new SymbolicRegressionFitness( data, constants ),
    new EliteSelection( ) );
// run one epoch of the population
population.RunEpoch( );
See Also