November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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182
Chapitre 7. Apprentissage d’ensemble et forêts aléatoires
7.1 CLASSIFICATEURS PAR VOTE
Supposons que vous ayez entraîné quelques classicateurs, chacun d’entre eux atteignant
une exactitude de 80% environ: il peut s’agir de classicateurs de type régression logis-
tique, SVM, forêt aléatoire, k plus proches voisins et quelques autres (voir gure 7.1).
Figure 7.1 – Entraînement de différents classificateurs
Un moyen très simple de créer un classicateur encore meilleur consiste à agréger
les prédictions de chacun des classicateurs et de prédire la classe qui obtient le plus
grand nombre de votes. Ce genre de classicateur à vote majoritaire ...
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