November 2019
Intermediate to advanced
320 pages
13h 35m
French
Content preview from Machine Learning avec Scikit-Learn
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9.2 Mélanges gaussiens
249
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qu’il puisse trouver un nombre quelconque de clusters de forme arbitraire, le fait
qu’il y ait très peu d’hyperparamètres à régler (juste un, le rayon des cercles, nom-
mé bandwidth) et enn le fait que l’algorithme repose sur une estimation de la
densité locale. Cependant, contrairement à DBSCAN, Mean-Shift a tendance à
découper les clusters en morceaux lorsqu’il existe des variations dans leur densité
interne. Malheureusement, sa complexité algorithmique est en O(m
2
), il n’est
donc pas approprié pour des jeux de données volumineux.
• Propagation d’afnité :
Cet ...
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