« Statistical relational learning » : différence entre les versions
(Page redirigée vers Apprentissage relationnel statistique) Balises : Nouvelle redirection Éditeur de wikicode 2017 |
m (Remplacement de texte : « ↵<small> » par « ==Sources== ») |
||
| (Une version intermédiaire par le même utilisateur non affichée) | |||
| Ligne 1 : | Ligne 1 : | ||
#REDIRECTION[[Apprentissage | #REDIRECTION[[Apprentissage statistique]] | ||
[[Catégorie:ENGLISH]] | [[Catégorie:ENGLISH]] | ||
| Ligne 8 : | Ligne 8 : | ||
is a subdiscipline of artificial intelligence and machine learning that is concerned with domain models that exhibit both uncertainty (which can be dealt with using statistical methods) and complex, relational structure.[291][292] Note that SRL is sometimes called Relational Machine Learning (RML) in the literature. Typically, the knowledge representation formalisms developed in SRL use (a subset of) first-order logic to describe relational properties of a domain in a general manner (universal quantification) and draw upon probabilistic graphical models (such as Bayesian networks or Markov networks) to model the uncertainty; some also build upon the methods of inductive logic programming. | is a subdiscipline of artificial intelligence and machine learning that is concerned with domain models that exhibit both uncertainty (which can be dealt with using statistical methods) and complex, relational structure.[291][292] Note that SRL is sometimes called Relational Machine Learning (RML) in the literature. Typically, the knowledge representation formalisms developed in SRL use (a subset of) first-order logic to describe relational properties of a domain in a general manner (universal quantification) and draw upon probabilistic graphical models (such as Bayesian networks or Markov networks) to model the uncertainty; some also build upon the methods of inductive logic programming. | ||
==Sources== | |||
[https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence Source : Wikipedia] | [https://en.wikipedia.org/wiki/Glossary_of_artificial_intelligence Source : Wikipedia] | ||
Dernière version du 28 janvier 2024 à 13:07
Rediriger vers :
Anglais
Statistical relational learning
is a subdiscipline of artificial intelligence and machine learning that is concerned with domain models that exhibit both uncertainty (which can be dealt with using statistical methods) and complex, relational structure.[291][292] Note that SRL is sometimes called Relational Machine Learning (RML) in the literature. Typically, the knowledge representation formalisms developed in SRL use (a subset of) first-order logic to describe relational properties of a domain in a general manner (universal quantification) and draw upon probabilistic graphical models (such as Bayesian networks or Markov networks) to model the uncertainty; some also build upon the methods of inductive logic programming.
Sources
Contributeurs: wiki
