Les arbres de décision sont aussi capables d’effectuer des tâches de régres-
sion. Construisons donc un arbre de régression en utilisant la classe
DecisionTreeRegressor de Scikit-Learn, en l’entraînant sur un jeu de don-
nées quadratique comportant des aléas (ou bruit) en utilisant max_depth=2 :
from sklearn.tree import DecisionTreeRegressor
tree_reg = DecisionTreeRegressor(max_depth=2)
tree_reg.fit(X, y)
La gure 6.4 présente l’arbre qui en résulte.
Figure 6.4– Arbre de décision pour une régression
Cet arbre ressemble beaucoup à l’arbre de classication construit ...
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