Missing data imputation through GTM as a mixture of \(t\)-distributions

DOI10.1016/j.neunet.2005.11.003zbMath1178.68472OpenAlexW2113121867WikidataQ31035597 ScholiaQ31035597MaRDI QIDQ858901

Alfredo Vellido

Publication date: 11 January 2007

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2005.11.003

zbMATH Keywords

outliersmissing datadata visualizationgenerative topographic mappingrobust imputationstudent multivariate \(t\)-distributions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Data structures (68P05)

Related Items

Advances in clustering and visualization of time series using GTM through time, Multivariate Student-\(t\) self-organizing maps, Variational Bayesian generative topographic mapping, Techniques for dealing with incomplete data: a tutorial and survey

Uses Software

• impute
• GTM

Cites Work

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