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Which of the following is a limitation of the K-means algorithm?

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Question: Which of the following is a limitation of the K-means algorithm?

Options:

  1. It can handle non-spherical clusters
  2. It requires the number of clusters to be specified in advance
  3. It is computationally efficient for large datasets
  4. It can be used for both supervised and unsupervised learning

Correct Answer: It requires the number of clusters to be specified in advance

Solution: 

A key limitation of K-means is that it requires the number of clusters to be specified beforehand, which can be challenging in practice.

Which of the following is a limitation of the K-means algorithm?

Practice Questions

Q1
Which of the following is a limitation of the K-means algorithm?
  1. It can handle non-spherical clusters
  2. It requires the number of clusters to be specified in advance
  3. It is computationally efficient for large datasets
  4. It can be used for both supervised and unsupervised learning

Questions & Step-by-Step Solutions

Which of the following is a limitation of the K-means algorithm?
Correct Answer: K-means requires the number of clusters to be specified beforehand.
  • Step 1: Understand what K-means is. K-means is a method used to group data into clusters.
  • Step 2: Know that K-means needs you to tell it how many clusters you want before it starts.
  • Step 3: Realize that deciding the right number of clusters can be difficult because you might not know how many groups are in your data.
  • Step 4: Recognize that this requirement to specify the number of clusters is a limitation of the K-means algorithm.
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