Databricks Certified Machine Learning - Associate
Get started today
Ultimate access to all questions.
In a dataset with a categorical feature 'Product Category', you have noticed that some values are missing. You have decided to use a classification model to predict the missing values based on other features in the dataset. Explain the process of using a classification model for imputation and discuss the potential benefits and limitations of this approach.
In a dataset with a categorical feature 'Product Category', you have noticed that some values are missing. You have decided to use a classification model to predict the missing values based on other features in the dataset. Explain the process of using a classification model for imputation and discuss the potential benefits and limitations of this approach.
Simulated
A
Using a classification model for imputation is not possible, as classification models require complete data to make predictions.
3.7%
B
Using a classification model for imputation involves training the model on the observed values of 'Product Category' and using it to predict the missing values. This approach can capture the relationships between 'Product Category' and other features, but may introduce bias if the model is not well-calibrated.
Comments
Loading comments...