Clustering with missing data: which equivalent for Rubin’s rules?

Vincent Audigier (1, 2) , Ndèye Niang (1)

1 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
2 CNAM - Conservatoire National des Arts et Métiers [CNAM]

Domaines: Méthodologie [stat.ME]

Vincent Audigier, Ndèye Niang. Clustering with missing data: which equivalent for Rubin’s rules?. Advances in Data Analysis and Classification, 2022, ⟨10.1007/s11634-022-00519-1⟩. ⟨hal-03766733⟩