AI-900 Question 96
Single answerA retail company wants to group its customers based on purchasing behavior to better target marketing campaigns. Which machine learning scenario would be most appropriate for this use case?
- A
Clustering
- B
Regression
- C
Classification
- D
Time-series forecasting
Show answer and explanation
Correct answer: A
Explanation
Clustering is a type of unsupervised machine learning used to group data points based on their similarities. In this scenario, the company wants to group customers based on their purchasing behavior, which is a natural fit for clustering. Unlike regression, classification, or time-series forecasting, clustering does not require predefined labels or target variables, making it the most appropriate solution for this use case.
- A. Correct.
Clustering is the correct approach for grouping similar customers based on their purchasing behavior, as it identifies natural groupings in the data without predefined labels.
- B. Incorrect.
Regression is used to predict a continuous numeric value, such as sales or revenue, and is not suited for grouping customers.
- C. Incorrect.
Classification is used to assign data points to predefined categories, such as predicting whether a customer will churn, but it does not group data without existing labels.
- D. Incorrect.
Time-series forecasting is used to predict future values based on time-ordered data, such as forecasting sales trends, and is unrelated to grouping customers.