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1. (This exercise is a variation of Exercise 10.2 in Chapter 10 of the textbook) 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), A2 (2,5), A3 (8, 4),B1(5,8),B2 (7,5 ), B3 (6,4),C1 (1,2),C2(4,9) The distance function is Euclidean distance. Suppose initially we assign A1, B1, and C1 as the center of each cluster, respectively. Run the k-means algorithm and show the clusters obtained during the first three iterations of the algorithm. First iteration: [Show More]

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