« Probabilité a posteriori » : différence entre les versions
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== Définition == | == Définition == | ||
La probabilité d'affectation des observations à des groupes d'après les données. | |||
== Français == | == Français == | ||
''' | ''' probabilité a posteriori ''' | ||
== Anglais == | == Anglais == | ||
''' | ''' posterior probability''' | ||
In statistics, the posterior probability expresses how likely a hypothesis is given a particular set of data. In terms of conditional probability, we can represent it in the following way: | In statistics, the posterior probability expresses how likely a hypothesis is given a particular set of data. In terms of conditional probability, we can represent it in the following way: | ||
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[https://deepai.org/machine-learning-glossary-and-terms/posterior-probability Source : DeepAI.org ] | [https://deepai.org/machine-learning-glossary-and-terms/posterior-probability Source : DeepAI.org ] | ||
[https://support.minitab.com/fr-fr/minitab/18/help-and-how-to/modeling-statistics/multivariate/supporting-topics/discriminant-analysis/what-are-posterior-and-prior-probabilities/ Source : Minitab.com ] | |||
[[Catégorie:DeepAI.org]] | [[Catégorie:DeepAI.org]] | ||
Version du 26 mars 2021 à 23:53
en construction
Définition
La probabilité d'affectation des observations à des groupes d'après les données.
Français
probabilité a posteriori
Anglais
posterior probability
In statistics, the posterior probability expresses how likely a hypothesis is given a particular set of data. In terms of conditional probability, we can represent it in the following way:
Posterior = P(H|D)
where D = data and H = hypothesis
This contrasts with the likelihood function, which is represented as P(D|H). This distinction is more of an interpretation rather than a mathematical property as both have the form of conditional probability. In order to calculate the posterior probability, we use Bayes theorem, which is discussed below.
Contributeurs: Arielle Halindintwali, Isaline Hodecent, wiki
