Question # 2. Clustering CLO3,4, PLO-1,2,3, C-1,3 16 Let’s suppose, there are seven data points {A, B, C, D, E, F and G} which lie on different locations. Table 2 describes the distance between given points which can be read horizontally or vertically. Table 2. A B C D E F G A 0 365 381 220 1325 808 673 B 365 0 225 575 995 730 320 C 381 225 0 590 970 948 415 D 220 575 590 0 1540 890 890 E 1325 995 970 1540 0 1462 710 F 808 730 948 890 1462 0 810 G 673 320 415 890 710 810 0 Use complete link agglomerative clustering to group the data points: Show the dendogram. Also tell the number of clusters at distance 300. Perform the k-mean clustering. Suppose that the initial seeds (centers of each cluster) are A, D and G. Run the k-means algorithm for 1 epoch only. At the end of epoch show the new clusters.
Question # 2. Clustering CLO3,4, PLO-1,2,3, C-1,3 16 Let’s suppose, there are seven data points {A, B, C, D, E, F and G} which lie on different locations. Table 2 describes the distance between given points which can be read horizontally or vertically. Table 2. A B C D E F G A 0 365 381 220 1325 808 673 B 365 0 225 575 995 730 320 C 381 225 0 590 970 948 415 D 220 575 590 0 1540 890 890 E 1325 995 970 1540 0 1462 710 F 808 730 948 890 1462 0 810 G 673 320 415 890 710 810 0 Use complete link agglomerative clustering to group the data points: Show the dendogram. Also tell the number of clusters at distance 300. Perform the k-mean clustering. Suppose that the initial seeds (centers of each cluster) are A, D and G. Run the k-means algorithm for 1 epoch only. At the end of epoch show the new clusters.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Question
Question # 2. Clustering |
CLO3,4, PLO-1,2,3, C-1,3 |
16 |
Let’s suppose, there are seven data points {A, B, C, D, E, F and G} which lie on different locations. Table 2 describes the distance between given points which can be read horizontally or vertically.
Table 2.
|
A |
B |
C |
D |
E |
F |
G |
A |
0 |
365 |
381 |
220 |
1325 |
808 |
673 |
B |
365 |
0 |
225 |
575 |
995 |
730 |
320 |
C |
381 |
225 |
0 |
590 |
970 |
948 |
415 |
D |
220 |
575 |
590 |
0 |
1540 |
890 |
890 |
E |
1325 |
995 |
970 |
1540 |
0 |
1462 |
710 |
F |
808 |
730 |
948 |
890 |
1462 |
0 |
810 |
G |
673 |
320 |
415 |
890 |
710 |
810 |
0 |
- Use complete link agglomerative clustering to group the data points: Show the dendogram. Also tell the number of clusters at distance 300.
- Perform the k-mean clustering. Suppose that the initial seeds (centers of each cluster) are A, D and G. Run the k-means
algorithm for 1 epoch only. At the end of epoch show the new clusters.
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