Visualizing a dissimilarity matrix
A dissimilarity matrix can be used as a measurement for the quality of a cluster. To visualize the matrix, we can use a heat map on a distance matrix. Within the plot, entries with low dissimilarity (or high similarity) are plotted darker, which is helpful to identify hidden structures in the data. In this recipe, we will discuss some techniques that are useful to visualize a dissimilarity matrix.
Getting ready
In order to visualize the dissimilarity matrix, you need to have the previous recipe completed by generating the customer dataset. In addition to this, a k-means object needs to be generated and stored in the variable km.
How to do it...
Perform the following steps to visualize the dissimilarity matrix:
- First, ...
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