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sume there is a dataset S={x(1),x(2),x(3),x(4),x(5)} where: x(1)=11,x(2)=9,x(3)=0,x(4)=5,x(5)=7. 1. If we have initial centroids c1=0,c2=11,c3=9 and perform K-means clustering algorithm on dataset S using Euclidean
sume there is a dataset S={x(1),x(2),x(3),x(4),x(5)} where: x(1)=11,x(2)=9,x(3)=0,x(4)=5,x(5)=7. 1. If we have initial centroids c1=0,c2=11,c3=9 and perform K-means clustering algorithm on dataset S using Euclidean distance. Fill in the table until the algorithm converges. You may not use all the rows. Some example entries are filled. For each of the iteration, find the positions of the centroids, assign the data points to the centroids, and compute the loss. (5 points) 2. Is the solution above optimal? If not, come up your own solution and fill in the optimal centroid positions, the optimal data points assignment in dataset S and the optimal loss.(3 points) What should we do to avoid solution in Q 2.1? (2 points)
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