scipy.optimize.minimize(fun, x0, args=(), method='trust-ncg', jac=None, hess=None, hessp=None, tol=None, callback=None, options={})

Minimization of scalar function of one or more variables using the Newton conjugate gradient trust-region algorithm.

See also

For documentation for the rest of the parameters, see scipy.optimize.minimize


initial_trust_radius : float

Initial trust-region radius.

max_trust_radius : float

Maximum value of the trust-region radius. No steps that are longer than this value will be proposed.

eta : float

Trust region related acceptance stringency for proposed steps.

gtol : float

Gradient norm must be less than gtol before successful termination.