Voir la source de Algorithme de majorité pondérée randomisée

==en construction==

== Définition ==
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== Français ==
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== Anglais ==
''' Randomized weighted majority algorithm'''

The randomized weighted majority algorithm is an algorithm in machine learning theory.[1] It improves the mistake bound of the weighted majority algorithm.

Imagine that every morning before the stock market opens, we get a prediction from each of our "experts" about whether the stock market will go up or down. Our goal is to somehow combine this set of predictions into a single prediction that we then use to make a buy or sell decision for the day. The RWMA gives us a way to do this combination such that our prediction record will be nearly as good as that of the single best expert in hindsight.



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[https://en.wikipedia.org/wiki/Randomized_weighted_majority_algorithm Source :  Source : Wikipedia  ]

[https://en.wikipedia.org/wiki/Outline_of_machine_learning#Machine_learning_algorithms  Source : Wikipedia Machine learning algorithms  ]

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[[Catégorie:Wikipedia-IA‏‎]]