Python scipy.optimize.minimize: ‘trust-constr’ and Hessian output

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SUMMARY

The discussion focuses on retrieving the Hessian matrix at the minimum when using the 'trust-constr' method in the Python scipy.optimize.minimize function. Users must calculate the Hessian manually by utilizing the 'hess' argument in the minimize function, as the default method is not specified in the documentation. This highlights a limitation in the scipy documentation regarding Hessian retrieval for the 'trust-constr' method.

PREREQUISITES
  • Familiarity with Python programming
  • Understanding of optimization concepts
  • Knowledge of the scipy library, specifically scipy.optimize
  • Basic understanding of Hessian matrices in optimization
NEXT STEPS
  • Explore the scipy.optimize.minimize documentation for detailed usage of the 'hess' argument
  • Learn how to implement custom Hessian functions in Python
  • Research optimization methods available in scipy, focusing on 'trust-constr'
  • Study numerical differentiation techniques for Hessian calculation
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Data scientists, machine learning practitioners, and Python developers who are working with optimization problems using the scipy library.

Joe Prendergast
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Hello, does anyone know how to retrieve the Hessian at the minimum when using method = ‘trust-constr’?
 
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Joe Prendergast said:
Hello, does anyone know how to retrieve the Hessian at the minimum when using method = ‘trust-constr’?
What software system does this question refer to?
 
renormalize said:
What software system does this question refer to?
Python as stated in my subject line. Specifically the scipy package.
 
Joe Prendergast said:
Python as stated in my subject line. Specifically the scipy package.
Thanks (sorry I overlooked your subject line!).
 
renormalize said:
Thanks (sorry I overlooked your subject line!).
Never hurts to repeat in the body of the post :)
 

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