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 *A*_{1}, *B*_{1}, and *C*_{1} 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 ...

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