Web: http://arxiv.org/abs/2201.12020

Jan. 31, 2022, 2:11 a.m. | Florian Mouret, Alexandre Hippert-Ferrer, Frédéric Pascal, Jean-Yves Tourneret

cs.LG updates on arXiv.org arxiv.org

This paper tackles the problem of missing data imputation for noisy and
non-Gaussian data. A classical imputation method, the Expectation Maximization
(EM) algorithm for Gaussian mixture models, has shown interesting properties
when compared to other popular approaches such as those based on k-nearest
neighbors or on multiple imputations by chained equations. However, Gaussian
mixture models are known to be not robust to heterogeneous data, which can lead
to poor estimation performance when the data is contaminated by outliers or
come …

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