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Module 5: Clustering

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K-medoids differs from K-means because K-medoids uses (i) An actual data point as the cluster representative (ii) The mean of all clusters (iii) A randomly generated point (iv) Eigenvectors

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Answer: (i) An actual data point as the cluster representative

K-medoids selects an observed data point (a medoid) as each cluster's representative. K-means uses the arithmetic mean, which need not be an actual data point.

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