Answer-first summary for fast verification
Answer: Unsupervised Learning
The correct answer is **Unsupervised Learning** (Option B). **Explanation:** - **Unsupervised Learning** is used when you have input data without labeled responses. The algorithm tries to find patterns and relationships in the data on its own. - **Reinforcement Learning** (Option A) involves an agent learning through trial and error interactions with an environment to maximize cumulative reward. - **Supervised Learning** (Option C) requires labeled training data where both input and output are provided. - **Semi-supervised Learning** (Option D) uses a combination of labeled and unlabeled data for training. Since the question doesn't specify whether the data is labeled or what type of learning problem it is, but the provided answer indicates B, this suggests the scenario likely involves finding patterns in unlabeled data, which is characteristic of unsupervised learning.
Author: Ritesh Yadav
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An e-commerce platform wants to group its customers into clusters based on purchase history and browsing behavior — but no labels exist
Which learning type should they use?
A
Reinforcement Learning
B
Unsupervised Learning
C
Supervised Learning
D
Semi-supervised Learning
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