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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.

この演習はコースの一部です

Unsupervised Learning in R

コースを見る

演習の手順

  • Fit a hierarchical clustering model to x using the hclust() function. Store the result in hclust.out.
  • Inspect the result with the summary() function.

実践的なインタラクティブ演習

このサンプルコードを完成させて、この演習に挑戦してみましょう。

# Create hierarchical clustering model: hclust.out
hclust.out <- ___

# Inspect the result
コードを編集して実行