Sharing pattern submodels for prediction with missing values. (arXiv:2206.11161v1 [cs.LG])

Web: http://arxiv.org/abs/2206.11161

Missing values are unavoidable in many applications of machine learning and
present a challenge both during training and at test time. When variables are
missing in recurring patterns, fitting separate pattern submodels have been
proposed as a solution. However, independent models do not make efficient use
of all available data. Conversely, fitting a shared model to the full data set
typically relies on imputation which may be suboptimal when missingness depends
on unobserved factors. We propose an alternative approach, called …

arxiv lg missing values prediction values