You are given five different data points, p1, p2, p3, p4, p5. Use the similarity matrix in Figure 2 to perform complete link hierarchical clustering. a) For each of the four merging steps, show the updated proximity matrix of the clusters. b) Visualize the clustering solution using a dendrogram. The dendrogram should clearly show the order in which the points are merged, and the distances between the clusters merged. c) Which clusters are formed if we need to have two clusters? Note: while the proximity table that is given to you has similarities, you can easily transform them into distances if you compute d = 1 - s. p1 22245 p2 p3 p4 p5 p1 1.00 0.10 0.41 0.55 0.35 T p2 0.10 1.00 0.64 0.47 0.98 p3 0.41 0.64 0.47 1.00 0.44 0.44 1.00 0.85 0.76 p4 0.55 ← p5 0.35 0.98 0.85 0.76 1.00
You are given five different data points, p1, p2, p3, p4, p5. Use the similarity matrix in Figure 2 to perform complete link hierarchical clustering. a) For each of the four merging steps, show the updated proximity matrix of the clusters. b) Visualize the clustering solution using a dendrogram. The dendrogram should clearly show the order in which the points are merged, and the distances between the clusters merged. c) Which clusters are formed if we need to have two clusters? Note: while the proximity table that is given to you has similarities, you can easily transform them into distances if you compute d = 1 - s. p1 22245 p2 p3 p4 p5 p1 1.00 0.10 0.41 0.55 0.35 T p2 0.10 1.00 0.64 0.47 0.98 p3 0.41 0.64 0.47 1.00 0.44 0.44 1.00 0.85 0.76 p4 0.55 ← p5 0.35 0.98 0.85 0.76 1.00
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
Related questions
Question
![You are given five different data points, p1, p2, p3, p4, p5. Use the similarity matrix in Figure 2 to
perform complete link hierarchical clustering.
a) For each of the four merging steps, show the updated proximity matrix of the clusters.
b) Visualize the clustering solution using a dendrogram. The dendrogram should clearly show the
order in which the points are merged, and the distances between the clusters merged.
c) Which clusters are formed we need to have two clusters?
Note: while the proximity table that is given to you has similarities, you can easily transform them into
distances if you compute d = 1 - s.
p1
p2
p3
p4
p5
p1
1.00
0.10
0.41
0.55
0.47
0.35 0.98
Figure 2: Proximity matrix (similarity)
p2
0.10
H
1.00
0.64
p3
0.41
0.64
1.00
0.44
0.85
L
p4
0.55
0.47
0.44
p5
0.35
0.98
0.85
0.76
1.00
1.00
0.76](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F447d2d1e-5623-43d2-90ca-f299e0b3a6fd%2Fc38de9f8-0524-4518-8710-314d6732b7cb%2Fkq88em_processed.jpeg&w=3840&q=75)
Transcribed Image Text:You are given five different data points, p1, p2, p3, p4, p5. Use the similarity matrix in Figure 2 to
perform complete link hierarchical clustering.
a) For each of the four merging steps, show the updated proximity matrix of the clusters.
b) Visualize the clustering solution using a dendrogram. The dendrogram should clearly show the
order in which the points are merged, and the distances between the clusters merged.
c) Which clusters are formed we need to have two clusters?
Note: while the proximity table that is given to you has similarities, you can easily transform them into
distances if you compute d = 1 - s.
p1
p2
p3
p4
p5
p1
1.00
0.10
0.41
0.55
0.47
0.35 0.98
Figure 2: Proximity matrix (similarity)
p2
0.10
H
1.00
0.64
p3
0.41
0.64
1.00
0.44
0.85
L
p4
0.55
0.47
0.44
p5
0.35
0.98
0.85
0.76
1.00
1.00
0.76
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