Microsoft Azure AI Fundamentals (AI-900) Practice Exam

Which type of model predicts outcomes based on input features?

1. Classification model

2. Regression model

3. Causal model

4. Descriptive model

The correct answer is: Classification model

A classification model is specifically designed to predict categorical outcomes based on input features. It assigns input data to one of several predefined classes or categories. This makes it particularly useful in scenarios such as determining whether an email is spam or not, or classifying images into different categories based on their content. On the other hand, a regression model, while also focused on predicting outcomes based on input features, is specifically aimed at continuous numerical outcomes. For instance, it could predict housing prices based on features like location, size, and number of rooms. Causal models seek to establish relationships and determine cause-effect dynamics rather than merely predicting categories or outcomes. Descriptive models focus on summarizing and interpreting existing data, rather than predicting future outcomes from input features. Thus, the defining characteristic of a classification model lies in its ability to categorize data based on input features, making it the correct choice in this context.