What is the result of applying mean imputation to a dataset with missing values?

Explanation

Mean imputation is a simple technique where missing entries in a numerical feature are filled with the arithmetic mean of the observed values in that column. Median imputation uses the median, while constant imputation uses a fixed value. Deletion refers to listwise deletion, which is a different strategy entirely.

Key points

Mean imputation uses the average of observed values
It is a simple, fast imputation method
It can reduce variance in the dataset

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