Microsoft Azure AI Fundamentals (AI-900) Practice Exam

What is the primary goal of a regression model in machine learning?

1. To classify data into categories

2. To predict a continuous outcome

3. To cluster similar items together

4. To categorize data into groups

The correct answer is: To predict a continuous outcome

The primary goal of a regression model in machine learning is to predict a continuous outcome. Regression is specifically designed to estimate the relationships among variables and to forecast the value of a dependent variable based on one or more independent variables. This is essential in various applications, such as predicting sales revenue, stock prices, or any other numerical value where the output is a continuous quantity. In contrast, classification models focus on sorting data into predefined categories, which relates to the first option and the last one. Clustering, mentioned in the third option, involves grouping similar items together without prior labeling, which is fundamentally different from the objectives of a regression model. The unique feature of regression lies in its ability to handle continuous data predictions, making it a critical tool in the machine learning repertoire for tasks requiring quantitative forecasting.