Mean Imputation involves replacing the missing values with the mean of the non-missing observations. If the data is non-symmetric, the median value can be imputed instead. Depending on the nature of the data, this might not be the best approach if the data is not missing completely at random, as it ignores the correlation structure between features.
What is Mean Imputation?
Mean Imputation involves replacing the missing values with the mean of the non-missing observations. If the data is non-symmetric, the median value can be imputed instead. Depending on the nature of the data, this might not be the best approach if the data is not missing completely at random, as it ignores the correlation structure between features.
Help us improve this post by suggesting in comments below:
– modifications to the text, and infographics
– video resources that offer clear explanations for this question
– code snippets and case studies relevant to this concept
– online blogs, and research publications that are a “must read” on this topic
Partner Ad
