Cluster I Distance labels Distance Cluster 2 Distance Distance labels 3 D56 D₁ 5 D₁, D57 3 13 D₁ D58 6 D₂ D59 I 9 D67 3

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Cluster I Distance labels Distance Cluster 2 Distance Distance labels 3 D56 D₁ 5 D₁, D57 3 13 D₁ D58 6 D₂ D59 I 9 D67 3

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Cluster I Distance Labels Distance Cluster 2 Distance Distance Labels 3 D56 D 5 D D57 3 13 D D58 6 D D59 I 9 D67 3 1
Cluster I Distance Labels Distance Cluster 2 Distance Distance Labels 3 D56 D 5 D D57 3 13 D D58 6 D D59 I 9 D67 3 1 (39.73 KiB) Viewed 18 times
Cluster I Distance labels Distance Cluster 2 Distance Distance labels 3 D56 D₁ 5 D₁, D57 3 13 D₁ D58 6 D₂ D59 I 9 D67 3 5 D68 D₁ 2 D69 5 D78 1 D79 2 D89 1 Q20) Assume we are trying to find the best K using the elbow approach. If we have two clusters Cluster 1 and cluster 2, cluster 1 has 4 instances il, i2, i3, and i4. Cluster 2 has 5 instances i5,16,17,18 and 19. The distance (indicated by D, which is the distance between instance i and instance j) between these instances in each cluster are given in the table below, what would be the value of W, (The average internal sum of squares for cluster 2) (3 marks) D₁ 4 7 2
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