Repeat Example 11.3 using other distances and types of linkage. Compare the results. Example 11.3 In this example, we show how to obtain the cophenetic correlation coefficient in MATLAB. We use the...


Repeat Example 11.3 using other distances and types of linkage. Compare the results.


Example 11.3


In this example, we show how to obtain the cophenetic correlation coefficient in MATLAB. We use the same small data set from the previous examples and calculate the cophenetic correlation coefficient when we have clusters based on different distances and linkages. First, we get the clusters using the following commands.


We now have four different cluster hierarchies. Their cophenetic correlation coefficients can be found from the following:


From this we get:


All of the resulting cophenetic correlation coefficients are large, with the largest corresponding to the complete linkage clustering based on the city block distance.


We now illustrate hierarchical clustering using a real data set that we have seen before. These data comprise measurements of a type of insect called Chaetocnema [Lindsey, Herzberg, and Watts, 1987; Hand, et al., 1994]. The variables measure the width of the first joint of the first tarsus, the width of the first joint of the second tarsus, and the maximal width of the aedegus. All measurements are in microns. We suspect that there are three species represented by these data, and we explore this in the next example.

Nov 14, 2021
SOLUTION.PDF

Get Answer To This Question

Related Questions & Answers

More Questions »

Submit New Assignment

Copy and Paste Your Assignment Here