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

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

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

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.

Steps: 4

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.

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

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