Question: What is the main difference between K-means and K-medoids?

Options:

1. K-means uses centroids, while K-medoids uses actual data points
2. K-medoids is faster than K-means
3. K-means can handle categorical data, while K-medoids cannot
4. There is no difference; they are the same algorithm

Correct Answer: K-means uses centroids, while K-medoids uses actual data points

Solution:

K-means uses centroids to represent clusters, while K-medoids uses actual data points as cluster representatives.