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- 3. Use the training data of Gauss2 example (Gauss2.train). (a). Run the K-means algorithm with K = 2 clusters and make a plot identifying the clusters. Also label the points with their known classes. = 2 clusters and make (b). Multiple all the x1 by 10. Run the K-means algorithm with K a plot identifying the clusters. Also label the points with their known classes. (c). Compare the class and cluster groupings for both plots in (a) and (b). Explain any differences between them. (d). Use agglomerative hierarchical clustering (hclust in the MASS library) to cluster the data, and divide them into 2 groups. You can use the function cutree to divide the clusters into 2 groups. Report on how the predicted cluster labels compare with actual cluster labels for each of the three methods for measuring distance between clusters, i.e. single linkage, complete linkage and average linkage. (e). Plot the dendrograms for the three methods in (d). What does the shape of the the dendrograms suggest about…,14 10. -13 A. D. Apply the sorted edges algorithm to the graph above. Give your answer as a list of vertices, starting and ending at vertex A. Example: ABCDEFA B.ment 7 Protected View Saved to this PC A Johl References Mailings Review View Help nternet can contain viruses. Unless you need to edit, it's safer to stay in Protected View. Enable Editing rd have been disabled, Reactivate 22. Apply the Sorted Edges algorithm. Answer by drawing the edges you use to create the circuit on the empty vetices on the right OR list the edges that you use to create the circuit on the line next to #22. 12 но E 13 10 6. 11 4 23. What is the weight of the circuit you found in #22? hp
