Having created our data frame,
df, we can begin to develop the clustering algorithms. We will start with hierarchical and then try our hand at k-means. After this, we will need to manipulate our data a little bit to demonstrate how to incorporate mixed data and conduct PAM.
To build a hierarchical cluster model in R, you can utilize the
hclust() function in the base
stats package. The two primary inputs needed for the function are a distance matrix and the clustering method. The distance matrix is easily done with the
dist() function. For the distance, we will use Euclidean distance. A number of clustering methods are available and the default for
hclust() is the complete linkage. We will try this, ...