A) In the distance matrix there is a missing distance x. Compute its value and write it. B) Consider two arbitrary clusters BDGH and ACEF. Compute and write the dissimilarity between these clusters under "complete linkage. C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output > KM$cluster [1] 1, 3, 2, 3, 3, 1, 3, 3 There is interest in determining the center of the cluster identified with the label 1. By computing this center manually or otherwise, identify which of the following is the correct centroid of this cluster:
A) In the distance matrix there is a missing distance x. Compute its value and write it. B) Consider two arbitrary clusters BDGH and ACEF. Compute and write the dissimilarity between these clusters under "complete linkage. C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output > KM$cluster [1] 1, 3, 2, 3, 3, 1, 3, 3 There is interest in determining the center of the cluster identified with the label 1. By computing this center manually or otherwise, identify which of the following is the correct centroid of this cluster:
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![A) In the distance matrix there is a missing distance x. Compute its value and write it.
B) Consider two arbitrary clusters BDGH and ACEF. Compute and write the dissimilarity between these clusters under "complete"
linkage.
C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output
> KM$cluster
[1] 1, 3, 2, 3, 3, 1, 3,
There is interest in determining the center of the cluster identified with the label 1. By computing this center manually or
otherwise, identify which of the following is the correct centroid of this cluster:
D) Still using the above data X, the R command pam (x=X, k=3)->PM was run, with the following output:
> PM$id.med
[1] 6, 2, 7
Identify correctly the medoids yielded by this cluster analysis.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F5a3c358f-b20b-40b2-995a-508219fdfa64%2F79619d26-cdb4-4b12-ab5f-ad415788e326%2F4qhnik_processed.png&w=3840&q=75)
Transcribed Image Text:A) In the distance matrix there is a missing distance x. Compute its value and write it.
B) Consider two arbitrary clusters BDGH and ACEF. Compute and write the dissimilarity between these clusters under "complete"
linkage.
C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output
> KM$cluster
[1] 1, 3, 2, 3, 3, 1, 3,
There is interest in determining the center of the cluster identified with the label 1. By computing this center manually or
otherwise, identify which of the following is the correct centroid of this cluster:
D) Still using the above data X, the R command pam (x=X, k=3)->PM was run, with the following output:
> PM$id.med
[1] 6, 2, 7
Identify correctly the medoids yielded by this cluster analysis.
Transcribed Image Text:Consider the following data set with n = 8 observations and p = 4 variables. The data set is given next
V1
V2 V3
V4
A
3.2 2.3
1
6.2
B
4.1 5.1 3.9
1.9
C
3.7
1.8 0.9 0.9
D
5.9 5 3.2
1.9
E
4.7 5.3
3.7
1
F
4.2 1.8
1
4
G 3.9 2.1
5.8
1.3
H 3.3 4.9 4.9 4.2
as well as the distance matrix using the "Manhattan" metric. The symbol x in the matrix below is to be calculated later.
A
B
C
D
E
F
G
H
A O
10.9
6.4
11.9
12.4 3.7
10.6 8.6
B
10.9
0
7.7
2.6
Χ
8.4
5.7 4.3
C
6.4 7.7
0
8.7
7.4
3.7
5.8
10.8
D
11.9 2.6
8.7
0
2.9
9.2
8.1
6.7
E
12.4
x
7.4
2.9
0
9.7
6.4
6.2
F
3.7
8.4
3.7
9.2
9.7
0
8.1 8.1
G
10.6 5.7
5.8
8.1
6.4
8.1
0
7.2
H
8.6
4.3
10.8
6.7
6.2
8.1
7.2 0
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Step 1: (A) Value of missing distance x:
VIEWStep 2: (B) Compute the dissimilarity between the clusters BDGH and ACEF using the “complete linkage”method:
VIEWStep 3: (C) The center of the cluster labeled 1 using the given output from the k-means clustering algorithm
VIEWStep 4: (D) Identify the medoids yielded by the PAM (Partitioning Around Medoids) cluster analysis:
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