MDFT Academy Quizzes

How should you process the column?

You are preparing a dataset for machine learning training. The dataset contains information about your customers, and includes a numerical age column. Some of the age values are set to ‘?’. This indicates that the age of this particular customer is not known.

How should you process the age column?

Choose the correct answer from the options below.

Please select at least one answer!

Congratulations, you are correct!

I'm sorry, your answer is not correct.

Remove the age column is incorrect. The age column contains important information and shouldn't be excluded as a training feature.
Train the machine learning model on all ages, including the '?' values is incorrect. Machine learning algorithms cannot train on rows containing missing data.
Replace all unknown ages with zero is incorrect. This will skew the distribution of the dataset and make it more difficult for the machine learning algorithm to generate good predictions.
Replace all unknown ages with the average customer age is correct

Replacing '?' with the average value is one of many strategies to process missing data. Check out my video lesson to learn more.

Learn about numerical data processing

1. Data Preparation

How should you process the column?