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Module 4: Cluster Analysis

20202m

Some telecommunication companies want to segment their customers into distinct groups in order to send appropriate subscription offers. This is an example of

(i) supervised learning
(ii) data extraction
(iii) serration
(iv) unsupervised learning

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Answer: (iv) unsupervised learning

Segmenting customers into distinct groups (clusters) in order to send appropriate subscription offers is a clustering task. Since the segments are not known in advance and the algorithm must discover the natural groupings from the data itself, this is unsupervised learning.

Why the others are wrong:

  • (i) supervised learning — that requires pre-labelled classes; here there are no pre-defined customer segment labels.
  • (ii) data extraction — a preprocessing/retrieval step, not the grouping task.
  • (iii) serration — a typo/nonsense option (no such data-mining category).

Hence customer segmentation for targeted offers is an example of unsupervised learning — option (iv).

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