Consider the following dataset consisting of the scores of two attributes on each of six objects: Object A1 A2 1.0 1.0 2 2.0 p.5 1.5 1.5 14 2.0 2.0 1.5 4.0 3.5 4.0 We want to group these objects into two dusters using K-means clustering. The distance between objects is the Manhattan distance. After the first iteration of K-means, clusters C1 and C2 have the following objects: C1 = ((1.0, 1.0), (2.0, 0.5)) C2= (15, 1.5), (2.0, 2.0L (1.5, 4.0). (3.5, 4.0]) What are the centroids after one further iteration? Select one: Oa. Centroid 1= [1.5, 0.75) Centroid 2= [2.125, 2.875)
Consider the following dataset consisting of the scores of two attributes on each of six objects: Object A1 A2 1.0 1.0 2 2.0 p.5 1.5 1.5 14 2.0 2.0 1.5 4.0 3.5 4.0 We want to group these objects into two dusters using K-means clustering. The distance between objects is the Manhattan distance. After the first iteration of K-means, clusters C1 and C2 have the following objects: C1 = ((1.0, 1.0), (2.0, 0.5)) C2= (15, 1.5), (2.0, 2.0L (1.5, 4.0). (3.5, 4.0]) What are the centroids after one further iteration? Select one: Oa. Centroid 1= [1.5, 0.75) Centroid 2= [2.125, 2.875)
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![Consider the following dataset consisting of the scores of two attributes on each of six objects:
Object#
A1
A2
1
1.0
1.0
12
2.0
0.5
1.5
1.5
4
2.0
2.0
15
1.5
4.0
3.5
4.0
We want to group these objects into two dusters using K-means clustering.
The distance between objects is the Manhattan distance.
After the first iteration of K-means, clusters C1 and C2 have the following objects:
C1 = ([1.0, 1.0), [2.0, 0.5)}
C2 = ([1.5, 1.5), [2.0, 2.01 (1.5, 4.0). [3.5, 4.0] )
What are the centroids after one further iteration?
Select one:
Centroid 1= [1.5, 0.75)
Centroid 2 = [2.125, 2.875)
Ob.
Centroid 1 = [1.75, 1]
Centroid 2 = [2.5, 3.75)]
Centroid 1 = [1.5, 1.0]
Centroid 2 = [2.33, 3.33]
%3D
Od.
Centroid 1 = [1.0, 1.0]
Centroid 2 = [3.5, 4.0]
Clear my choice](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fd99b6acb-3c56-46a2-8aaf-762988209417%2F4cba8be0-fb47-44cb-9bec-907744bb4626%2F5v4c2k_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Consider the following dataset consisting of the scores of two attributes on each of six objects:
Object#
A1
A2
1
1.0
1.0
12
2.0
0.5
1.5
1.5
4
2.0
2.0
15
1.5
4.0
3.5
4.0
We want to group these objects into two dusters using K-means clustering.
The distance between objects is the Manhattan distance.
After the first iteration of K-means, clusters C1 and C2 have the following objects:
C1 = ([1.0, 1.0), [2.0, 0.5)}
C2 = ([1.5, 1.5), [2.0, 2.01 (1.5, 4.0). [3.5, 4.0] )
What are the centroids after one further iteration?
Select one:
Centroid 1= [1.5, 0.75)
Centroid 2 = [2.125, 2.875)
Ob.
Centroid 1 = [1.75, 1]
Centroid 2 = [2.5, 3.75)]
Centroid 1 = [1.5, 1.0]
Centroid 2 = [2.33, 3.33]
%3D
Od.
Centroid 1 = [1.0, 1.0]
Centroid 2 = [3.5, 4.0]
Clear my choice
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