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1 2 3 4 5 6 1 2 0.12 3 0.51 0.25 4 0.84 0.16 0.14 0 5 0.28 0.77 0.70 0.45 6 0.34 0.61 0.93 0.20 0.67 Table 1: Euclidean Distance Matrix

1 2 3 4 5 6 1 2 0.12 3 0.51 0.25 4 0.84 0.16 0.14 0 5 0.28 0.77 0.70 0.45 6 0.34 0.61 0.93 0.20 0.67 Table 1: Euclidean Distance Matrix

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Given an input Euclidean distance matrix of size 6 by 6, as shown in Table 1.

 

 

 

 

Table 1: Euclidean Distance Matrix

1.      Perform single linkage-hierarchical clustering (agglomerative) and draw the dendrogram

2.      Perform complete linkage-hierarchical clustering (agglomerative) and draw the dendrogram.

3.      How to determine the optimal number of clusters from the dendrogram? Show in your dendrograms.

4.      If you are using K-mean clustering, how to determine the optimal number of clusters?

1 4 5 6 2 0.12 0.51 0.25 4 0.84 0.16 0.14 0.28 0.77 0.70 0.45 0 6 0.34 0.61 0.93 0.20 0.67 Table 1: Euclidean Distance Matrix 3. 2. 3. 5.
Transcribed Image Text:1 4 5 6 2 0.12 0.51 0.25 4 0.84 0.16 0.14 0.28 0.77 0.70 0.45 0 6 0.34 0.61 0.93 0.20 0.67 Table 1: Euclidean Distance Matrix 3. 2. 3. 5.
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