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The algorithm decorator currently allows arbitrary attributes, and therefore different usage within models, datasets, networks and systems. Thereby the internal organisation is facilitated by the attribute 'category', which, however is used differently within different contexts.
Code redundancy and code scattering can be avoided by providing different specific decoratos, like: inference for mean values, correlations etc. estimand for optimization objective for scalar evaluation functions
The text was updated successfully, but these errors were encountered:
fishroot
changed the title
restucture code: specify the algorithm decorator
Use specific function decorators for different algorithm categories
Nov 25, 2018
The algorithm decorator currently allows arbitrary attributes, and therefore different usage within models, datasets, networks and systems. Thereby the internal organisation is facilitated by the attribute 'category', which, however is used differently within different contexts.
Code redundancy and code scattering can be avoided by providing different specific decoratos, like: inference for mean values, correlations etc.
estimand for optimization
objective for scalar evaluation functions
The text was updated successfully, but these errors were encountered: