Chapitre 9. Techniques d’apprentissage non supervisé
Toutefois, nous avons choisi arbitrairement le nombre de partitions k et nous pouvons
certainement faire mieux. Étant donné que les k-moyennes constituent seulement une
étape de prétraitement dans un pipeline de classication, il est beaucoup plus simple que
précédemment de trouver une bonne valeur pour k : il n’y a pas besoin d’effectuer une
analyse de silhouette ou de minimiser l’inertie, car la meilleure valeur de k est simplement
celle qui donne les meilleurs résultats de classication durant la validation croisée. Nous
pouvons utiliser GridSearchCV pour trouver le nombre de clusters ...
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