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Missing Data and Imputation Methods in Partition of Variables

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.
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https://hal.archives-ouvertes.fr/hal-01124926
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Submitted on : Friday, March 6, 2015 - 10:52:54 AM
Last modification on : Thursday, March 26, 2020 - 11:39:43 AM

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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 Berlin Heidelberg, pp.631-637, 2004, Studies in Classification, Data Analysis,, ⟨10.1007/978-3-642-17103-1_59⟩. ⟨hal-01124926⟩

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