minimize(method=’trust-krylov’)#
- scipy.optimize.minimize(fun, x0, args=(), method=None, jac=None, hess=None, hessp=None, bounds=None, constraints=(), tol=None, callback=None, options=None)
- Minimization of a scalar function of one or more variables using a nearly exact trust-region algorithm that only requires matrix vector products with the hessian matrix. - Added in version 1.0.0. - See also - For documentation for the rest of the parameters, see - scipy.optimize.minimize- Options:
- ——-
- inexactbool, optional
- Accuracy to solve subproblems. If True requires less nonlinear iterations, but more vector products.