AI-900 Question 99
Single answerYou are analyzing customer purchasing behavior for an e-commerce platform. The goal is to group customers based on similarities in their buying patterns, such as the types of products they typically purchase and the frequency of purchases. Which machine learning scenario is most appropriate for this task?
- A
Clustering
- B
Regression
- C
Classification
- D
Reinforcement Learning
Show answer and explanation
Correct answer: A
Explanation
The task described in the scenario involves identifying natural groups or clusters of customers based on their purchasing behaviors. Clustering is a type of unsupervised learning that is ideal for scenarios where there are no predefined labels and the goal is to discover patterns or groupings within the data. Other machine learning approaches, such as regression, classification, or reinforcement learning, do not align with the requirements of this task.
- A. Correct.
Clustering is the correct answer because it is used to group data points (in this case, customers) based on their similarities without predefined labels.
- B. Incorrect.
Regression is incorrect because it is used to predict continuous numerical values, such as sales revenue or temperature, and not for grouping data.
- C. Incorrect.
Classification is incorrect because it is used to categorize data into predefined labels or classes, such as 'high-value customer' or 'low-value customer,' whereas the scenario involves discovering groups without predefined categories.
- D. Incorrect.
Reinforcement Learning is incorrect because it focuses on training an agent to make sequential decisions in an environment to maximize a reward, which is unrelated to the task of grouping customers.