Question: Suppose that the data mining task is to cluster points (with ((x, y)) representing location) into three clusters, where the points are [A_{1}(2,10), A_{2}(2,5), A_{3}(8,4),
Suppose that the data mining task is to cluster points (with \((x, y)\) representing location) into three clusters, where the points are
\[A_{1}(2,10), A_{2}(2,5), A_{3}(8,4), B_{1}(5,8), B_{2}(7,5), B_{3}(6,4), C_{1}(1,2), C_{2}(4,9) \text {. }\]
The distance function is Euclidean distance. Suppose initially we assign \(A_{1}, B_{1}\), and \(C_{1}\) as the center of each cluster, respectively. Use the \(k\)-means algorithm to show only
a. The three cluster centers after the first round of execution.
b. The final three clusters.
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To perform the kmeans clustering algorithm we need to follow these steps 1 Assign initial centroids ... View full answer
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