Databricks Certified Machine Learning - Associate
Get started today
Ultimate access to all questions.
Ultimate access to all questions.
In a dataset with a categorical feature 'Occupation', you have noticed that some values are missing. You have decided to use multiple imputation to fill in the missing values. Explain the process of multiple imputation and discuss the potential benefits and limitations of this approach.
Explanation:
Option A is correct. Multiple imputation involves creating multiple imputed datasets by filling in the missing values with different plausible values and analyzing each dataset separately. This approach can capture the uncertainty in the imputed values and provide more robust results by accounting for the variability in the imputations. However, there are potential limitations, such as being computationally expensive and requiring specialized software. Additionally, the choice of imputation method and the number of imputed datasets can significantly impact the results.