Extreme Value Imputation: Replace the missing values with an arbitrary value located at the far end of the distribution of the feature, for example 999. This would not be a recommended approach for a linear model but sometimes works well with decision tree algorithms, as if there is predictive power of the missingness, a decision tree would be able to utilize the extremity of the coding to harness that predictability.
What is Extreme Value Imputation?
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