Assume the following dataset is given:
Assume the following dataset is given:
 (2,2), (4,4), (5,5), (6,6), (8,8),(9,9), (0,4), (4,0) .
K-Means is used with k=4 to cluster the dataset.
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Moreover, Manhattan distance is used as the distance function (formula below) to compute distances between centroids and objects in the dataset.
D ((x1, x2), (x1', x2')) = |x1-x1'| + |x2-x2|
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Further assume that K-Means's initial clusters C1, C2, C3, and C4 are as follows:
C1: {(2, 2), (4, 4), (6, 6)}Â Â Â Â
C2: {(0, 4), (4, 0)}
C3: {(5, 5), (9, 9)}
C4: {(8, 8}}
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Now apply the K-means algorithm and show the centroids and the clusters for each iteration.
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Posted 12 Oct 2017 12:10 PM
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