Missing Data and Imputation Methods in Partition of Variables

[DSB04] Missing Data and Imputation Methods in Partition of Variables

Conférence Internationale avec comité de lecture : Classification, Clustering and Data Mining Applications, D.Banks et al. editors,, January 2004, pp. 631-637, Series Studies in Classification, Data Analysis, , (IXth Conference of the International Federation of Classification Societies, Juillet 2004, Chicago)

Auteurs: , G. Saporta , H. Bacelar-Nicolau

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Résumé: We deal with the effect of missing data under a "missing at random model" on clasification of variables with non-hierarchical methods. The partitions are compared by the Rand's index.

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@inproceedings {
	DSB04,
	title	=	"{Missing Data and Imputation Methods in Partition of Variables}",
	author	=	" and G. Saporta and H. Bacelar-Nicolau ",
	booktitle	=	"{Classification, Clustering and Data Mining Applications, D.Banks et al. editors,}",
	year	=	2004,
	month	=	"January",
	series	=	"Studies in Classification, Data Analysis, ",
	pages	=	" 631-637",
	note	=	"{IXth Conference of the International Federation of Classification Societies, Juillet 2004, Chicago}",
}