MixMI, a mixture of Gaussian-process and linear-regression imputers with individualized mixing weights, reports lower mean absolute scaled error than six benchmarks on all four datasets tested.
Comparison of imputation methods for missing laboratory data in medicine,
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Mixture-based Multiple Imputation Model for Clinical Data with a Temporal Dimension
MixMI, a mixture of Gaussian-process and linear-regression imputers with individualized mixing weights, reports lower mean absolute scaled error than six benchmarks on all four datasets tested.