minimize(method=’trust-ncg’)¶
- 
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- Options
- initial_trust_radiusfloat
- Initial trust-region radius. 
- max_trust_radiusfloat
- Maximum value of the trust-region radius. No steps that are longer than this value will be proposed. 
- etafloat
- Trust region related acceptance stringency for proposed steps. 
- gtolfloat
- Gradient norm must be less than gtol before successful termination. 
 
 
