In the k-means clustering method, clusters are created around ________.

• A. Mean
• B. Mode
• C. Median
• D. Maximum

Answer: (A)

In k-means, each cluster is organized around its centroid, which is the mean of all points assigned to that cluster. The algorithm repeatedly assigns each point to the nearest centroid and then recalculates each centroid as the average of the points in that cluster. This choice of the mean is deliberate because the mean minimizes the sum of squared distances from the points to the center, aligning exactly with what k-means optimizes. So the clusters form around the mean.

The other options aren’t used as the central point in standard k-means: the median would correspond to a different objective (minimizing sum of absolute deviations, as in k-medians), the mode isn’t a robust center for continuous data, and the maximum isn’t a meaningful center for clustering.