Clustering belongs to which learning paradigm?
Show answer and explanation
Answer: B
Clustering groups records so that items within a group are more similar to each other than to items in other groups. No labels are provided during training, so the algorithm discovers structure from the feature values themselves, which places it squarely in unsupervised learning. The analyst usually interprets and names the resulting groups afterwards. Because there is no correct answer to compare against, evaluation relies on measures of separation and cohesion or on business usefulness.
Why the other options are wrong
- A. Supervised learning requires labelled examples, which clustering does not use.
- C. Reinforcement learning learns from reward signals through interaction with an environment, not from grouping static records.
- D. Semi-supervised learning combines a small labelled set with a larger unlabelled one; clustering uses no labels at all.
Exam tip. Grouping without labels equals unsupervised.