agglomerativeclustering dendrogram

What is a dendrogram in agglomerative clustering?
Dendrograms are a diagrammatic representation of the hierarchical relationship between the data-points.
It illustrates the arrangement of the clusters produced by the corresponding analyses and is used to observe the output of hierarchical (agglomerative) clustering.
What is Agglomerative approach of clustering?
There are two major types of approaches in hierarchical clustering: Agglomerative clustering: Divide the data points into different clusters and then aggregate them as the distance decreases.
Divisive clustering: Combine all the data points as a single cluster and divide them as the distance between them increases.
The key to interpreting a dendrogram is to focus on the differences in height among the branches.
Objects that are located at the same height level share similar characteristics with each other.
While objects that are located at varying height levels do not share similar characteristics.

How do you cut a dendrogram in hierarchical clustering?

Hierarchical clustering does not tell us how many clusters there are, or where to cut the dendrogram to form clusters.
In R there is a function cutttree which will cut a tree into clusters at a specified height.
However, based on our visualization, we might prefer to cut the long branches at different heights.

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