Microsoft Azure AI Fundamentals (AI-900) Practice Exam

What method involves grouping items by their common characteristics?

1. Classification

2. Clustering

3. Regression

4. Labeling

The correct answer is: Clustering

The concept of clustering is about grouping items based on their shared characteristics or similarities without prior knowledge of the group labels. This method is widely used in machine learning for tasks such as market segmentation, social network analysis, and organization of computing clusters. In clustering, algorithms analyze the data by identifying patterns and similarities among the data points, effectively categorizing them into distinct groups or clusters. For example, in a customer segmentation scenario, clustering can be used to identify distinct groups of customers based on their purchasing behaviors or attributes, allowing businesses to tailor their marketing strategies for each segment. While classification involves assigning predefined labels to data points based on learned characteristics from a labeled training set, clustering does not require labels and is used primarily for exploratory data analysis. Regression focuses on predicting continuous outcomes rather than grouping items, and labeling involves tagging or categorizing items with specific identifiers rather than determining their grouping based on similarity. Thus, clustering is specifically the correct approach for grouping items by common characteristics.