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CS Professional · Artificial Intelligence, Data Analytics and Cyber Security - Laws and Practice · Artificial Intelligence - Introduction and Basics

A retailer feeds unlabelled purchase histories of two million customers into an algorithm that, without any predefined categories, groups them into segments of similar buying behaviour. A compliance officer asks which statement correctly describes this technique.

It is unsupervised learning, with clustering as the typical task. The algorithm receives unlabelled data and discovers customer segments by itself without predefined categories or reward signals. Supervised learning needs labelled outcomes, and reinforcement learning needs rewards, so neither fits.

  1. AIt is unsupervised learning, and clustering is a typical taskCorrect
  2. BIt is supervised learning, because the output is a segment label
  3. CIt is reinforcement learning, because the algorithm improves with each customer
  4. DIt is a reactive machine, because it keeps no data

Explanation

No labels or target outcomes are supplied, and the algorithm discovers structure itself, which defines unsupervised learning; grouping similar items is clustering. The segment names are produced by the algorithm, not provided in training, so the supervised option is wrong. No reward signal exists, ruling out reinforcement learning.

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