Editing Algorithmic learning theory (section)

{{Short description|Framework for analyzing machine learning algorithms}}
{{Refimprove|date=January 2021}}

'''Algorithmic learning theory''' is a mathematical framework for analyzing 
[[machine learning]] problems and algorithms. Synonyms include '''formal learning theory''' and '''algorithmic inductive inference'''{{citation needed|date=January 2021}}. Algorithmic learning theory is different from [[statistical learning theory]] in that it does not make use of statistical assumptions and analysis. Both algorithmic and statistical learning theory are concerned with machine learning and can thus be viewed as branches of [[computational learning theory]]{{citation needed|date=January 2021}}.