Types in MathNet.Numerics.Optimization.ObjectiveFunctions

Type ForwardDifferenceGradientObjectiveFunction

Namespace MathNet.Numerics.Optimization.ObjectiveFunctions

Interfaces IObjectiveFunction

Adapts an objective function with only value implemented to provide a gradient as well. Gradient calculation is done using the finite difference method, specifically forward differences. For each gradient computed, the algorithm requires an additional number of function evaluations equal to the functions's number of input parameters.




Public Constructors

ForwardDifferenceGradientObjectiveFunction(IObjectiveFunction valueOnlyObj, Vector<T> lowerBound, Vector<T> upperBound, double relativeIncrement, double minimumIncrement)

Public Methods

IObjectiveFunction CreateNew()

bool Equals(object obj)

void EvaluateAt(Vector<T> point)

IObjectiveFunction Fork()

int GetHashCode()

Type GetType()

string ToString()

Public Properties

Vector<T> Gradient get; set;

Matrix<T> Hessian get;

IObjectiveFunction InnerObjectiveFunction get; set;

bool IsGradientSupported get;

bool IsHessianSupported get;

double MinimumIncrement get; set;

Vector<T> Point get; set;

double RelativeIncrement get; set;

double Value get;