10.1 Briefly describe and give examples of each of the following approaches to clustering: partitioning methods, hierarchical methods, density-based methods, and grid-based methods.
10.2 Suppose that the data mining task is to cluster points (with (x, y) representing location) into three clusters, where the points are
The distance function is Euclidean distance. Suppose initially we assign A1, B1, and C1 as the center of each cluster, respectively. Use the k-means algorithm to show only
(a) The three cluster centers after the first round of execution.
(b) The final three clusters.
10.3 Use an example to show why the k-means algorithm ...