November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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9.1 Partitionnement
245
© Dunod – Toute reproduction non autorisée est un délit.
Avant de passer aux modèles de mélange gaussien, jetons un coup d’œil à
DBSCAN, un autre algorithme de partitionnement très apprécié qui s’appuie sur une
approche très différente basée sur l’estimation de la densité locale. Cette approche
permet à l’algorithme d’identier des clusters de forme arbitraire.
9.1.6 DBSCAN
Cet algorithme dénit les clusters comme des régions continues de haute densité.
Voici comment cela fonctionne :
• Pour chaque observation, l’algorithme compte combien d’observations sont
situées à moins de
ϵ
(epsilon) de celle-ci. Cette zone s’appelle ...
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