LeastSquaresOptimizer Class

Represents an algorithm that minimizes a sum of squares.

Definition

Namespace: Extreme.Mathematics.Optimization
Assembly: Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.23

public abstract class LeastSquaresOptimizer : ManagedIterativeAlgorithm<Vector<double>>

Visual Basic

Public MustInherit Class LeastSquaresOptimizer
	Inherits ManagedIterativeAlgorithm(Of Vector(Of Double))

C++/CLI

public ref class LeastSquaresOptimizer abstract : public ManagedIterativeAlgorithm<Vector<double>^>

[<AbstractClassAttribute>]
type LeastSquaresOptimizer = 
    class
        inherit ManagedIterativeAlgorithm<Vector<float>>
    end

Inheritance: Object → ManagedIterativeAlgorithm<Vector<Double>, Double, SolutionReport<Vector<Double>, Double>> → ManagedIterativeAlgorithm<Vector<Double>> → LeastSquaresOptimizer

Derived: Extreme.Mathematics.Optimization.LevenbergMarquardtOptimizer
Extreme.Mathematics.Optimization.TrustRegionReflectiveOptimizer

Remarks

The LeastSquaresOptimizer class serves as the abstract base class for implementations of nonlinear least squares optimizers. This class cannot be instantiated. Instead, use one of its inherited classes:

Class	Description
LevenbergMarquardtOptimizer	Represents an optimizer that implements the Levenberg-Marquardt algorithm.
TrustRegionReflectiveOptimizer	Represents an optimizer that uses the Trust Region Reflective algorithm.

To verify that the algorithm terminated normally, you can inspect the Status property, which is of type AlgorithmStatus. A value of Converged indicates that the algorithm terminated normally. However, it is still possible that the algorithm didn't converge to the actual best fit. A visual inspection is always recommended.

Constructors

LeastSquaresOptimizer

Constructs a new LeastSquaresOptimizer object.

Properties

ConvergenceTests	Gets the collection of convergence tests for the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Dimensions	Gets or sets the number of dimensions of the optimization problem.
EstimatedError	Gets a value indicating the size of the absolute error of the result. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
EvaluationsNeeded	Gets the number of evaluations needed to execute the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
EvaluationsRemaining	Gets the number of evaluations still available. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Extremum	Gets or sets the current best approximation to the extremum. Obsolete.
GradientTest	Gets the VectorConvergenceTest<T> that uses the gradient of the objective function.
GradientVector	Gets or sets the current value of the gradient.
HasSharedDegreeOfParallelism	Indicates whether the degree of parallelism is a property that is shared across instances. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
InitialGuess	Gets or sets the initial value for the iteration.
InitialTrustRegionSize	Gets or sets the initial size of the trust region.
IterationsNeeded	Gets the number of iterations needed by the algorithm to reach the desired accuracy. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
IterationsRemaining	Gets the number of iterations remaining. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
JacobianEvaluationsNeeded	Gets or sets the number of times the Jacobian was evaluated.
JacobianFunction	Gets or sets a delegate that computes the Jacobian of the problem.
LastCorrection	Gets the last correction to the solution of the system of equations.
LowerBounds	Gets or sets the vector of lower bounds for the solution.
MaxDegreeOfParallelism	Gets or sets the maximum degree of parallelism enabled by this instance. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MaxEvaluations	Gets or sets the maximum number of evaluations during the calculation. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MaxIterations	Gets or sets the maximum number of iterations to use when approximating the roots of the target function. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Minimum	Gets or sets the current best approximation to the minimum.
MinimumValue	Gets or sets the current value of the objective function.
MinIterations	Gets or sets the minimum iterations that have to be performed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
NumberOfFunctions	Gets or sets the number of functions in the problem.
ObjectiveFunction	Gets or sets a delegate that computes the function values of the problem.
ParallelOptions	Gets or sets the configuration for the parallel behavior of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Result	Gets the result of an algorithm after it has executed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SolutionReport	Gets the result of an algorithm after it has executed. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SolutionTest	Gets the VectorConvergenceTest<T> that uses the approximate solution.
Status	Gets the AlgorithmStatus following an execution of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThrowExceptionOnFailure	Gets or sets a value indicating whether to throw an exception when the algorithm fails to converge. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
UpperBounds	Gets or sets the upper bounds for the solution.
ValueAtExtremum	Gets or sets the current value of the objective function. Obsolete.
ValueTest	Gets the SimpleConvergenceTest<T> that uses the value of the target functions.
VarianceCovarianceMatrix	Gets the variance-covariance matrix of the solution.

Methods

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)
FindMinimum	Runs the Levenberg-Marquardt algorithm and returns the result.
GetHashCode	Serves as the default hash function. (Inherited from Object)
GetType	Gets the Type of the current instance. (Inherited from Object)
GetVarianceCovarianceMatrix	Computes the variance-covariance matrix of the solution.
IncrementEvaluations()	Increments the number of evaluations by one. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
IncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Iterate	Performs one iteration of the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Iterated	Performs tasks after the iteration is completed, but before the status of the algorithm is finalized. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object)
OnConvergence	Performs any tasks after the main algorithm has converged. (Overrides ManagedIterativeAlgorithm<T, TError, TReport>.OnConvergence())
OnFailure	Performs any tasks after the main algorithm has failed to converge. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
OnInit	Performs initialization before the first iteration. (Overrides ManagedIterativeAlgorithm<T, TError, TReport>.OnInit())
ReportFailure	Records the results of an algorithm in case it fails. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ReportResult	Records the results of an algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ReportSuccess	Records the results of a algorithm that converged successfully. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ResetEvaluations	Resets the number of evaluations to zero. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Restart	Prepares the algorithm to be run again with possibly different inputs. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Run()	Runs the algorithm. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
Run(ParallelOptions)	Runs the algorithm using the specified parallelization options. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SetMinimumValue	Sets the value of the objective function at the minimum to the supplied value.
SetResult	Sets the results of an algorithm's execution. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
SetSymbolicObjectiveFunction(Expression<Func<Vector<Double>, Double>>[])	Sets the objective function as a list of symbolic expressions.
SetSymbolicObjectiveFunction(IList<Expression<Func<Vector<Double>, Double>>>)	Sets the objective function as a list of symbolic expressions.
TestConvergence	Checks whether the algorithm has converged. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThreadSafeIncrementEvaluations()	Increments the number of evaluations by one. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThreadSafeIncrementEvaluations(Int32)	Increments the number of evaluations by the specified amount. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ThrowConvergenceException	Interprets the AlgorithmStatus and throws the appropriate exception. (Inherited from ManagedIterativeAlgorithm<T, TError, TReport>)
ToString	Returns a string that represents the current object. (Inherited from Object)