November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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188
Chapitre 7. Apprentissage d’ensemble et forêts aléatoires
array([[0.31746032, 0.68253968],
[0.34117647, 0.65882353],
[1. , 0. ],
...
[1. , 0. ],
[0.03108808, 0.96891192],
[0.57291667, 0.42708333]])
7.3 PARCELLES ALÉATOIRES
ET SOUS-ESPACES ALÉATOIRES
La classe BaggingClassifier permet aussi de tirer au sort les variables. Les deux
hyperparamètres max_features et bootstrap_features permettent de
contrôler ce tirage au sort. Ils fonctionnent de la même façon que les hyperparamètres
max_samples et bootstrap, mais pour sélectionner des variables au lieu de sélec-
tionner des observations. Chaque prédicteur sera donc entraîné sur un sous-ensemble ...
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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.