Hierarchical clustering with results
In this exercise, you will create your first hierarchical clustering model using the hclust()
function.
We have created some data that has two dimensions and placed it in a variable called x
. Your task is to create a hierarchical clustering model of x
. Remember from the video that the first step to hierarchical clustering is determining the similarity between observations, which you will do with the dist()
function.
You will look at the structure of the resulting model using the summary()
function.
This exercise is part of the course
Unsupervised Learning in R
Exercise instructions
- Fit a hierarchical clustering model to
x
using thehclust()
function. Store the result inhclust.out
. - Inspect the result with the
summary()
function.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create hierarchical clustering model: hclust.out
hclust.out <- ___
# Inspect the result