Skip to Main content Skip to Navigation
Book sections

Missing Data and Imputation Methods in Partition of Variables

Ana Lorga da Silva 1 Gilbert Saporta 2 Helena Bacelar-Nicolau 3
1 Universidade Lusófona de Humanidades e Tecnologias [Lisbon]
2 CEDRIC - MSDMA - CEDRIC. Méthodes statistiques de data-mining et apprentissage
CEDRIC - Centre d'études et de recherche en informatique et communications
3 ULISBOA - Universidade de Lisboa
Abstract : 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.
Document type :
Book sections
Complete list of metadata

Cited literature [9 references]  Display  Hide  Download
https://hal.archives-ouvertes.fr/hal-01124926
Contributor : Laboratoire Cedric <>
Submitted on : Friday, June 12, 2020 - 12:46:32 PM
Last modification on : Thursday, June 18, 2020 - 9:38:07 AM

File

Vignette du document
RC662.pdf
Files produced by the author(s)

Identifiers

Collections

CNAM | INSMI | CEDRIC-CNAM

Citation

Ana Lorga da Silva, Gilbert Saporta, Helena Bacelar-Nicolau. Missing Data and Imputation Methods in Partition of Variables. Classification, Clustering, and Data Mining Applications, Springer, pp.631-637, 2004, Studies in Classification, Data Analysis and Knowledge Organisation, ⟨10.1007/978-3-642-17103-1_59⟩. ⟨hal-01124926⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

377

Files downloads

174