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Machine Learning Practice · End Term · 13 Sept 2026 · May 2026 term

Question 27: A company uses K-Means clustering to divide its customer…

Question 27

+4 marksOne or more correct options

A company uses K-Means clustering to divide its customers into 4 groups based on their purchasing behavior. After training the model, the data science team observes the following:
Two different runs of K-Means on the same dataset produce different customer groups. One cluster contains customers that are much farther away from their assigned cluster center compared to other clusters.
Which of the following statements are most likely to explain these observations?

Select all that apply.

  1. A

    K-Means can converge to different solutions because the initial placement of cluster centroids can affect the final clusters.

  2. B

    The cluster with customers far from its centroid may indicate that the chosen value of K does not represent the natural grouping structure of the data.

  3. C

    K-Means guarantees finding the globally optimal clustering solution regardless of initialization.

  4. D

    K-Means assigns clusters by maximizing the distance between points within the same cluster.

Show answer

Correct answers

  • A

    K-Means can converge to different solutions because the initial placement of cluster centroids can affect the final clusters.

  • B

    The cluster with customers far from its centroid may indicate that the chosen value of K does not represent the natural grouping structure of the data.

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Question 27 of 30 in the IIT Madras BS Machine Learning Practice (MLP) End Term paper sat on 13 Sept 2026, in the May 2026 term (Machine Learning Practice 13 Sep 26). It carries 4 marks.

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