/Impute-missing-data-with-XGBoost

When signaficant amount of data in highly-important features are missing, what can we do? Impute the missing data with mean or median? In this Juyter notebook, I demonstrate embedding a XGBoost model to do the data imputation in the data transformer.

Primary LanguageJupyter Notebook

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