C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output > KM$cluster [1] 1, 3, 2, 1, 3, 1, 2 There is interest in determining the center of the cluster identified with the label 3. By computing this center manually or otherwise, identify which of the following is the correct centroid of this cluster: D) Still using the above data X, the R command pam (x=X, k=3) ->PM was run, with the following output: > PM$id.med [1] 1, 7, 6 Identify correctly the medoids yielded by this cluster analysis. Consider the following data set with n = 7 observations and p = 3 variables. The data set is given next V1 V2 V3 A 2.7 4.3 3.3 B 3.2 6.2 2 # X с 1.9 3.1 5.3 D 2.2 4.1 4 E 2 5.8 2.1 F 6.3 3.8 3.8 G 2.7 0.9 5.3 as well as the distance matrix using the “Euclidean” metric. The symbol x in the matrix below is to be calculated later. B F G с DE 2.356 2.466 0.883 2.045 3.669 4.711 3.068 X 4.314 1.667 4.188 4.701 2.341 3.945 6.263 2.557 4.116 3.49 5.038 5.894 4.86 A A 0 B 2.356 0 C 2.466 4.711 0 D 0.883 3.068 1.667 0 E 2.045 4.188 2.557 0 F 3.669 4.314 4.701 4.116 5.038 0 G 3.945 6.263 2.341 3.49 A) In the distance matrix there is a missing distance x. Compute its value and write it. 5.894 4.86 0 B) Consider two arbitrary clusters ABDEFG and C. Compute and write the dissimilarity between these clusters under "single” linkage.
C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output > KM$cluster [1] 1, 3, 2, 1, 3, 1, 2 There is interest in determining the center of the cluster identified with the label 3. By computing this center manually or otherwise, identify which of the following is the correct centroid of this cluster: D) Still using the above data X, the R command pam (x=X, k=3) ->PM was run, with the following output: > PM$id.med [1] 1, 7, 6 Identify correctly the medoids yielded by this cluster analysis. Consider the following data set with n = 7 observations and p = 3 variables. The data set is given next V1 V2 V3 A 2.7 4.3 3.3 B 3.2 6.2 2 # X с 1.9 3.1 5.3 D 2.2 4.1 4 E 2 5.8 2.1 F 6.3 3.8 3.8 G 2.7 0.9 5.3 as well as the distance matrix using the “Euclidean” metric. The symbol x in the matrix below is to be calculated later. B F G с DE 2.356 2.466 0.883 2.045 3.669 4.711 3.068 X 4.314 1.667 4.188 4.701 2.341 3.945 6.263 2.557 4.116 3.49 5.038 5.894 4.86 A A 0 B 2.356 0 C 2.466 4.711 0 D 0.883 3.068 1.667 0 E 2.045 4.188 2.557 0 F 3.669 4.314 4.701 4.116 5.038 0 G 3.945 6.263 2.341 3.49 A) In the distance matrix there is a missing distance x. Compute its value and write it. 5.894 4.86 0 B) Consider two arbitrary clusters ABDEFG and C. Compute and write the dissimilarity between these clusters under "single” linkage.
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![C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output
> KM$cluster
[1] 1, 3, 2, 1, 3, 1, 2
There is interest in determining the center of the cluster identified with the label 3. By computing this center manually or otherwise, identify which of the
following is the correct centroid of this cluster:
D) Still using the above data X, the R command pam (x=X, k=3) ->PM was run, with the following output:
> PM$id.med
[1] 1, 7, 6
Identify correctly the medoids yielded by this cluster analysis.](https://content.bartleby.com/qna-images/question/acdab16c-d90f-4903-947d-823b5c8c50a8/04971822-7b1d-4f3a-af69-4cf37e3560cb/5hkkw1_processed.jpeg)
Transcribed Image Text:C) Using the above data X, the R command KM<-kmeans (x=X, centers=3) was run, with the following output
> KM$cluster
[1] 1, 3, 2, 1, 3, 1, 2
There is interest in determining the center of the cluster identified with the label 3. By computing this center manually or otherwise, identify which of the
following is the correct centroid of this cluster:
D) Still using the above data X, the R command pam (x=X, k=3) ->PM was run, with the following output:
> PM$id.med
[1] 1, 7, 6
Identify correctly the medoids yielded by this cluster analysis.
Transcribed Image Text:Consider the following data set with n = 7 observations and p = 3 variables. The data set is given next
V1 V2 V3
A 2.7 4.3 3.3
B 3.2 6.2 2
#
X
с 1.9 3.1 5.3
D 2.2 4.1 4
E 2 5.8 2.1
F 6.3 3.8 3.8
G 2.7 0.9 5.3
as well as the distance matrix using the “Euclidean” metric. The symbol x in the matrix below is to be calculated later.
B
F
G
с DE
2.356 2.466 0.883 2.045 3.669
4.711 3.068 X
4.314
1.667 4.188 4.701 2.341
3.945
6.263
2.557 4.116 3.49
5.038 5.894
4.86
A
A 0
B 2.356 0
C 2.466 4.711 0
D 0.883 3.068 1.667 0
E 2.045
4.188 2.557 0
F 3.669 4.314 4.701 4.116 5.038 0
G
3.945 6.263 2.341 3.49
A) In the distance matrix there is a missing distance x. Compute its value and write it.
5.894 4.86 0
B) Consider two arbitrary clusters ABDEFG and C. Compute and write the dissimilarity between these clusters under "single” linkage.
