What are some common data imputation techniques?

What are some common data imputation techniques?

Common data imputation techniques include mean, median, mode imputation, k-nearest neighbors, and regression imputation.

Can you explain how k-nearest neighbors imputation works?

K-nearest neighbors imputation replaces missing values with the average of the k closest data points in the feature space.

What are the advantages of using regression imputation?

Regression imputation can provide more accurate estimates by leveraging relationships between variables, but it assumes linearity.

Are there any drawbacks to using mean imputation?

Yes, mean imputation can reduce variability and may not be suitable for skewed distributions, leading to biased results.