Discover the correct use case for classification in Azure AI fundamentals. Our AI expert provides a clear explanation with examples to help you master key concepts for the AI-900 certification exam.
Table of Contents
Question
Select the correct use case from provided scenarios for classification.
A. Analyzing the contents of images and grouping images that have similar colors.
B. Predicting how many minutes it will take someone to run a race based on past race times.
C. Predicting whether someone uses a bicycle to travel to work based on the distance from home to work.
D. Predicting how many cups of coffee a person will drink based on how many hours the person slept the previous night.
Answer
The correct use case for classification among the provided scenarios is:
C. Predicting whether someone uses a bicycle to travel to work based on the distance from home to work.
Explanation
Classification is a supervised machine learning technique used to predict which category or class an input belongs to, based on training data. In this scenario, the model would be trained on data about people’s commuting habits and the distance between their home and work. It would learn to classify each person into one of two classes: “bicycles to work” or “does not bicycle to work”, based on the input feature of home-to-work distance.
The other scenarios are not ideal use cases for classification:
A) Analyzing image contents and grouping by color is an unsupervised learning task known as clustering, not classification.
B) and D) Predicting numeric values like race times or cups of coffee consumed based on inputs is a regression task, which predicts continuous quantities rather than discrete classes.
So in summary, only C represents a proper use case for binary classification, predicting one of two possible class labels based on input data. Recognizing these key distinctions is crucial for applying the appropriate Azure AI techniques to solve different problems.
In machine learning, classification is a task where the goal is to assign an item into one of a set of predefined categories. This involves predicting discrete labels, such as “yes/no,” “true/false,” or categories like “cat/dog.”
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.