Question A1: Using the Euclidean distance formula, compute the distance between D1 and M1.

A.

9.7

B.

9.0

C.

16.5

D.

17.0

Question A2: Using the Euclidean distance formula, compute the distance between D1 and M2.

A.

9.0

B.

9.7

C.

17.0

D.

16.5

Question A3:

Based on the answers for Questions A1 and A2, D1 should be placed in cluster 2.

Select one:

True

False

Question A4:

In building a k-means clustering model, the process of identifying the suitable value of k is referred to as identifying the elbow of the Within Sum of Squares (WSS) curve.

Select one:

True

False

Question A5: A good clustering model possesses properties of _____________ (high similarity within each group) and _____________ (low similarity between each group).

A.

external separation; internal cohesion

B.

external cohesion; internal separation

C.

internal cohesion; external separation

D.

internal separation; external cohesion

Questions A1 to A5 are based on the following information: Consider the following dataset which consists of five devices, and each device is explained by three features, i.e. Feature X, Feature Y, and Feature Z. Assuming that k- means clustering analysis will be developed based on this dataset and the two clusters are identified with the respective centroids as follows: centroid for cluster 1, M1 = {1.0, 1.0, 1.0), centroid for cluster 2, M2 = {15.0, 15.0. 15.0}. Feature Z Device D1 Feature X 8.7 6.4 Feature Y 6.9 1.5 12.4 D2 D3 4.6 9.3 10.4 7.4 10.8 9.9 2.5 D4 2.2 3.6 D5 11.2