Imputation

Category: science

The technique used to replace missing data points in a dataset.

Data in the real world is always messy and missing. Imputation is the "educated guess." If a client’s age is missing, we might use the "mean" of all other customers to fill that gap. It allows the model to keep running without discarding perfectly good rows.

Common Examples

• We performed mean-based imputation to handle the missing occupation fields, ensuring our pricing model didn’t reject these rows.
• Imputation is a critical pre-processing step; doing it poorly can introduce significant bias into the resulting model predictions.