November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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7.5 Boosting
191
© Dunod – Toute reproduction non autorisée est un délit.
Sans importance
Très important
Figure 7.6 – Importance des pixels des images MNIST
(définie par un classificateur de forêt aléatoire)
Les forêts aléatoires sont très pratiques pour comprendre rapidement quelles
variables ont réellement de l’importance, en particulier si vous devez les sélectionner.
7.5 BOOSTING
Le boosting (appelé initialement hypothesis boosting, c’est-à-dire renforcement d’hypo-
thèse) désigne toute méthode d’ensemble qui peut combiner plusieurs mauvais élèves en
un bon élève. L’idée générale de la plupart des méthodes de boosting est d’entraîner des
prédicteurs ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.