Exploring the branches cut from the tree

The cutree() function you used in exercises 5 & 6 can also be used to cut a tree at a given height by using the h parameter. Take a moment to explore the clusters you have generated from the previous exercises based on the heights 20 & 40.

This exercise is part of the course

Cluster Analysis in R

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Exercise instructions

Build the cluster assignment vector clusters_h20 using cutree() with a h = 20.
Append the cluster assignments as a column cluster to the lineup data frame and save the results to a new data frame called lineup_h20_complete.
Repeat the above two steps for a height of 40, generating the variables clusters_h40 and lineup_h40_complete.
Use ggplot2 to create a scatter plot, colored by the cluster assignment for both heights.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

dist_players <- dist(lineup, method = 'euclidean')
hc_players <- hclust(dist_players, method = "complete")

# Calculate the assignment vector with a h of 20
clusters_h20 <- ___

# Create a new data frame storing these results
lineup_h20_complete <- mutate(lineup, cluster = ___)

# Calculate the assignment vector with a h of 40
clusters_h40 <- ___

# Create a new data frame storing these results
lineup_h40_complete <- ___

# Plot the positions of the players and color them using their cluster for height = 20
ggplot(___, aes(x = ___, y = ___, color = factor(___))) +
  geom_point()

# Plot the positions of the players and color them using their cluster for height = 40

Edit and Run Code