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Found 2 papers, 2 papers with code
Linear predictor on linearly-generated data with missing values: non consistency and solutions
In the particular Gaussian case, it can be written as a linear function of multiway interactions between the observed data and the various missing-value indicators.
On the consistency of supervised learning with missing values
A striking result is that the widely-used method of imputing with a constant, such as the mean prior to learning is consistent when missing values are not informative.
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