Use the k-means algorithm and Euclidean distance to cluster the following 10 examples into 3 clusters: Assume
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Question:
Use the k-means algorithm and Euclidean distance to cluster the following 10 examples into 3 clusters:
Assume that the initial clusters are A, E and H.
Pt | X1 | X2 |
A | 1 | 2 |
B | 8 | 5 |
C | 4 | 9 |
D | 2 | 4 |
E | 9 | 7 |
F | 5 | 9 |
G | 3 | 5 |
H | 6 | 9 |
I | 4 | 4 |
J | 7 | 9 |
a Develop a 10x10 distance metric for the above dataset.
b. Perform K-Means clustering and show all the calculations performed at each iteration.
c. Draw a 10 by 10 space with all the 10 points and show the clusters and the new centroids after each iteration.
Related Book For
Discrete Mathematics and Its Applications
ISBN: 978-0073383095
7th edition
Authors: Kenneth H. Rosen
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