Théorème No Free Lunch
en construction
Définition
Français
théorème No Free Lunch
théorème NFL
théorème « Rien n'est gratuit! »
Anglais
No Free Lunch theorem
NFL theorem
The No Free Lunch Theorem, often abbreviated as NFL or NFLT, is a theoretical finding that suggests all optimization algorithms perform equally well when their performance is averaged over all possible objective functions.
There are, generally speaking, two No Free Lunch (NFL) theorems: one for machine learning and one for search and optimization. These two theorems are related and tend to be bundled into one general axiom (the folklore theorem).
TANSTAFL - there ain't no such thing as a free lunch.
Contributeurs: Jean Benoît Morel, wiki
