Neural networks and predictive matching for flexible imputation

Let be a data matrix, with entries partly missing in the last columns. A problem of practical relevance is that of imputing the missing values in such an incomplete data set. We propose to use (partially) predictive matching coupled with a flexible fit, such as provided by a neural network. The merits and demerits of the approach suggested are discussed.

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