Skip to content

ACCA Strategic Professional · Strategic Business Leader · Machine learning, AI and robotics

Dalton Insurance feeds its entire customer database, with no outcome labels, into an algorithm that groups customers into segments with similar behaviour. The board then asks how the segments should be treated. Which statement is most appropriate?

The segments are patterns discovered by unsupervised learning, so management must interpret and validate them. There were no labelled outcomes or predefined correct answers, so the algorithm cannot confirm that the groups are meaningful or useful for business decisions.

  1. AThe segments are verified outputs because the algorithm was trained on correct answers
  2. BThe segments are discovered patterns that management must interpret and validate, because no predefined target existedCorrect
  3. CThe approach is reinforcement learning because the algorithm improves with each customer
  4. DThe approach is supervised learning because customers are placed into categories

Explanation

Clustering on unlabelled data is unsupervised learning. The algorithm finds structure but does not know what the groups mean, so human judgement is needed to interpret and validate them. Placing items in groups does not make it supervised, because supervised learning needs labelled targets.

Did you get it right without looking?

One question tells you little. A timed set on Machine learning, AI and robotics shows your real accuracy, how long you take and where you lose marks.

More Machine learning, AI and robotics questions