# AI-900: How to Use Regression Models to Predict Numeric Values

Learn how to use regression models to predict numeric values in AI-900 exam. Find out which scenarios can be solved by regression and which cannot.

## Question

Which of the following scenarios can be resolved by using a regression model?

A. Predict selling price of a car using data like engine size, mileage, number of seats etc.
B. Predict daily rental demand of bicycles by using historic data.
C. Predict yearly income of customers based on their occupation, age, education etc.
D. Determine if patients with some pre-existing conditions are more likely to suffer from diabetes.

A. Predict selling price of a car using data like engine size, mileage, number of seats etc.
B. Predict daily rental demand of bicycles by using historic data.
C. Predict yearly income of customers based on their occupation, age, education etc.

## Explanation

Regression is a form of machine learning that is used to predict a numeric label based on an item’s features

A regression model is a type of supervised machine learning that is used to predict numeric values, such as prices, demand, income, etc. Regression models learn the relationship between input features and a continuous target variable, and then use this relationship to make predictions on new data.

The scenarios that can be resolved by using a regression model are A, B, and C, because they all involve predicting a numeric value based on some input features. For example, a regression model can predict the selling price of a car using data like engine size, mileage, number of seats, etc. Similarly, a regression model can predict the daily rental demand of bicycles or the yearly income of customers using historic data and other relevant features.

The scenario that cannot be resolved by using a regression model is D, because it involves determining a binary outcome, such as yes or no, rather than a numeric value. This is a classification problem, not a regression problem. A classification model is another type of supervised machine learning that is used to predict discrete categories, such as labels, classes, or groups. For example, a classification model can determine if patients with some pre-existing conditions are more likely to suffer from diabetes by assigning them a probability of having the disease.

Microsoft Azure AI Fundamentals AI-900 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Microsoft Azure AI Fundamentals AI-900 exam and earn Microsoft Azure AI Fundamentals AI-900 certification.

### Alex Lim

Alex Lim is a certified IT Technical Support Architect with over 15 years of experience in designing, implementing, and troubleshooting complex IT systems and networks. He has worked for leading IT companies, such as Microsoft, IBM, and Cisco, providing technical support and solutions to clients across various industries and sectors. Alex has a bachelor’s degree in computer science from the National University of Singapore and a master’s degree in information security from the Massachusetts Institute of Technology. He is also the author of several best-selling books on IT technical support, such as The IT Technical Support Handbook and Troubleshooting IT Systems and Networks. Alex lives in Bandar, Johore, Malaysia with his wife and two chilrdren. You can reach him at [email protected] or follow him on Website | Twitter | Facebook