« Recherche de règles d'association » : différence entre les versions


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Balise : Éditeur de wikicode 2017
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Balise : Éditeur de wikicode 2017
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[[Catégorie:Intelligence artificielle]]
[[Catégorie:Intelligence artificielle]]
[[Catégorie:vocabulary]]  
[[Catégorie:vocabulary]]  




== Définition ==
== Définition ==
 
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== Français ==
== Français ==
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== Anglais ==
== Anglais ==
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'''Association Rule Learning'''


discovering rules for observing A given B. This is closely related to clustering in that we’re attempting to find connections between events. However, the difference is the approach. Instead of drawing bounds on a region and seeing if someone fits in that bucket, we use the frequency of a collection of discrete observations to create priors: what’s the probability of observing A, or B, or C? From these, we figure out what the probability is of observing A given B, or observing C given A and B. This is just Bayesian statistics: P(A), P(B | A), P(C | A, B), and so forth.
discovering rules for observing A given B. This is closely related to clustering in that we’re attempting to find connections between events. However, the difference is the approach. Instead of drawing bounds on a region and seeing if someone fits in that bucket, we use the frequency of a collection of discrete observations to create priors: what’s the probability of observing A, or B, or C? From these, we figure out what the probability is of observing A given B, or observing C given A and B. This is just Bayesian statistics: P(A), P(B | A), P(C | A, B), and so forth.

Version du 17 septembre 2019 à 09:12

en construction


Définition

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Français

...

Anglais

Association Rule Learning

discovering rules for observing A given B. This is closely related to clustering in that we’re attempting to find connections between events. However, the difference is the approach. Instead of drawing bounds on a region and seeing if someone fits in that bucket, we use the frequency of a collection of discrete observations to create priors: what’s the probability of observing A, or B, or C? From these, we figure out what the probability is of observing A given B, or observing C given A and B. This is just Bayesian statistics: P(A), P(B | A), P(C | A, B), and so forth.


Machine Learning for Beginners – a How-to Guide https://opendatascience.com/machine-learning-for-beginners/