The graph provided below displays the distribution of each of the thirteen features. What three features will influence the distance calculation the most?

Hierarchical clustering is usually defined as an optimization problem

The result of a clustering algorithm can be used to perform classification.

Consider the proximity matrix provided below.

     A       B       C        D

A   0       3       2.2      1

B   3       0      1.41     3.16

C  2.2    1.41   0         2

D 1       3.16   2         0

What instances should be joined when average link is used?

Consider the proximity matrix provided below.

     A       B       C        D

A   0       3       2.2      1

B   3       0      1.41     3.16

C  2.2    1.41   1        2

D 1       3.16   2         0

Does the proximity matrix contain any errors?

Consider the dendrogram illustrated below. If a horizontal line is drawn at 3.5 how many clusters will be formed?

Assume that the K-medoid clustering algorithm has been applied to a data set described by two descriptive features. The table below shows the instances assigned to cluster 1. What is the ID of the instance that should represent the cluster? Assume that Manhattan distance is used.

ID   d1   d2

4     3     4

5     6     2

9     6     4

13   7     3

15   7     4

17   7     6

19   8     5

Which of the following best describes the steps involved in the k-means++ initialization process?

What is a significant advantage of using the X-Means clustering algorithm over the standard k-means algorithm?