A data analyst is using supervised machine learning to study the relationship between advertising budget (in ₹) and sales revenue (in ₹) for a retail company.

Question

A data analyst is using supervised machine learning to study the relationship between advertising budget (in ₹) and sales revenue (in ₹) for a retail company.
He uses linear regression to predict sales based on the advertising budget. Later, he wants to predict whether a customer will make a purchase (Yes/No) based on features like age, income and browsing time.
Which of the following statements correctly distinguishes regression from classification in these contexts?

Accepted Answer

Regression uses continuous dependent variables, while classification uses discrete dependent variables.

Answer

Regression models cannot be used for numerical data, whereas classification models can.

Answer

Regression minimises the difference between predicted and actual class labels, while classification minimises the mean squared error.

Answer

Regression predicts categorical outputs, while classification predicts numerical values.

A data analyst is using supervised machine learning to study the relationship between advertising budget (in ₹) and sales revenue (in ₹) for a retail company.

From BEL PE Computer Science PYQ, 20 Dec 2025 (5:00 PM)