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0. Assume, you want to cluster 7 observations into 3 clusters using K-Means clustering algorithm. After first iteration the clusters: C1,C2,C3 has the following observartions: C1: {(1,1), (4,4), (7,7)} C2: {(0,4), (4,0)} C3: {(5,5), (9,9)} What will be the Manhattan distance for observation (9,9) from cluster centroid C1 in the second iteration?
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