BroydenFletcherGoldfarbShanno Properties

The number of corrections to approximate the inverse Hessian matrix. Default is 6. Values less than 3 are not recommended. Large values will result in excessive computing time.

Delta for convergence test.

Epsilon for convergence test.

Gets or sets the function to be optimized.

The machine precision for floating-point values.

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

A parameter to control the accuracy of the line search routine.

The line search algorithm.

The maximum number of iterations.

The maximum number of trials for the line search.

The maximum step of the line search.

The minimum step of the line search routine.

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

Coefficient for the L1 norm of variables.

End index for computing L1 norm of the variables.

Start index for computing L1 norm of the variables.

A parameter to control the accuracy of the line search routine. The default value is 1e-4. This parameter should be greater than zero and smaller than 0.5.

Distance for delta-based convergence test.

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

Get the exit code returned in the last call to the Maximize or Minimize methods.

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

Gets the output of the function at the current Solution.

A coefficient for the Wolfe condition.