November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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178
Chapitre 6. Arbres de décision
Figure 6.8 – Sensibilité aux détails du jeu d’entraînement
Les forêts aléatoires peuvent limiter cette instabilité en effectuant une moyenne
des prédictions sur de nombreux arbres, comme nous le verrons au chapitre suivant.
6.10 EXERCICES
1. Quelle est la profondeur approximative d’un arbre de décision
entraîné (sans restrictions) sur un jeu d’entraînement comportant
1million d’observations?
2. L’impureté Gini d’un nœud est-elle en général inférieure ou
supérieure à celle du nœud parent? Est-elle généralement inférieure/
supérieure ou toujours inférieure/supérieure?
3. Si un arbre de décision surajuste le ...
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