In centroid-based clustering, which step assigns each point to the nearest centroid based on a distance measure?

In centroid-based clustering, which step assigns each point to the nearest centroid based on a distance measure?

• A. Recalculation
• B. Initialization
• C. Euclidean distance
• D. Allocation

Answer: (D)

Allocation is the step where each data point is assigned to the cluster whose centroid is closest according to the chosen distance metric. In centroid-based clustering like k-means, the process alternates between assigning points to the nearest centroid and recalculating centroids based on current assignments. The distance measure (often Euclidean distance) decides which centroid a point is closest to, and that decision is executed during the allocation step. Recalculation updates the centroid positions after assignments, initialization chooses the starting centroids, and Euclidean distance is a metric used to judge proximity rather than an actionable step.

Allocation is the step where each data point is assigned to the cluster whose centroid is closest according to the chosen distance metric. In centroid-based clustering like k-means, the process alternates between assigning points to the nearest centroid and recalculating centroids based on current assignments. The distance measure (often Euclidean distance) decides which centroid a point is closest to, and that decision is executed during the allocation step. Recalculation updates the centroid positions after assignments, initialization chooses the starting centroids, and Euclidean distance is a metric used to judge proximity rather than an actionable step.