Nearest Neighbor Imputation: Replace the missing values with the average of the observation’s k-nearest neighbors. Unlike simple mean or mode imputation, this approach does account for the correlation structure of the features; however, it can be sensitive to outliers and is more time consuming on large datasets.
What is Nearest Neighbor Imputation?
Nearest Neighbor Imputation: Replace the missing values with the average of the observation’s k-nearest neighbors. Unlike simple mean or mode imputation, this approach does account for the correlation structure of the features; however, it can be sensitive to outliers and is more time consuming on large datasets.
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
