K-mean clustering algorithm has clustered the given 8 observations into 3…
2019
K-mean clustering algorithm has clustered the given 8 observations into 3 clusters after 1st iteration as follows:
𝐶1 : {(3,3),(5,5),(7,7)}
𝐶2 : {(0,6),(6,0),(3,0)}
𝐶3 : {(8,8),(4,4)}
What will be the Manhattan distance for observation (4,4) from cluster centroid 𝐶1 in the second iteration?
Answer: A. \(2\) — Answer: 2 Step 1: Find the centroid of cluster C1 by averaging the x and y coordinates of its members (3,3), (5,5), (7,7). The centroid is ( (3+5+7)/3 ,…
- A.
\(2\) - B.
\(\sqrt 2\) - C.
\(0\) - D.
\(18\)
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Correct answer: A
Answer: 2
Step 1: Find the centroid of cluster C1 by averaging the x and y coordinates of its members (3,3), (5,5), (7,7). The centroid is ( (3+5+7)/3 , (3+5+7)/3 ) = (5,5).
Step 2: Compute the Manhattan distance between the observation (4,4) and the centroid (5,5). Manhattan distance = |4-5| + |4-5| = 1 + 1 = 2.
Therefore the Manhattan distance for (4,4) from the centroid of C1 in the second iteration is 2.
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