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.
Cet exercice fait partie du cours
Unsupervised Learning in R
Instructions
- Fit a hierarchical clustering model to
x
using thehclust()
function. Store the result inhclust.out
. - Inspect the result with the
summary()
function.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
# Create hierarchical clustering model: hclust.out
hclust.out <- ___
# Inspect the result