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2004 | OriginalPaper | Buchkapitel

Missing Data and Imputation Methods in Partition of Variables

verfasst von : Ana Lorga da Silva, Gilbert Saporta, Helena Bacelar-Nicolau

Erschienen in: Classification, Clustering, and Data Mining Applications

Verlag: Springer Berlin Heidelberg

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We deal with the effect of missing data under a “Missing at Random Model” on classification of variables with non-hierarchical methods. The partitions are compared by the Rand index.

Metadaten
Titel
Missing Data and Imputation Methods in Partition of Variables
verfasst von
Ana Lorga da Silva
Gilbert Saporta
Helena Bacelar-Nicolau
Copyright-Jahr
2004
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-17103-1_59