Dendrogram

A dendrogram is a network structure. It is constituted of a root node that gives birth to several nodes connected by edges or branches. The last nodes of the hierarchy are called leaves.

Two type of dendrogram exist, resulting from 2 types of dataset:

1- A hierarchic dataset provides the links between nodes explicitly.
2- The result of a clustering algorithm can be visualized as a dendrogram.

Dendrograms are often used to depict the strength of clustering in a matrix. In other words, it shows the hierarchical relationship between objects.

The greater the difference in height, the more dissimilarity. But in some dendrograms, shape and color are also used to help people recognize hierarchy and clusters faster.

Pro:

-Good to allocate objects to clusters.

-The height of the branches often shows similarity/dissimilarity between two objects.

Con:

-The shape of the dendrogram does not explicitly decide the total amount of existing clusters. It cannot tell you how many clusters you should have.

-The height that shows similarity is not always true to original data.

-One two objects join they cannot be seperated.

Calculation: Hierarchical Clustering Algorithms

Dendrogram is usually the visual output of hierarchical clustering. Hierarchical clustering can be performed with either a distance matrix or raw data.

Examples of algorithms used for clustering methods: single linkage, complete linkage, simple average, centroid, median, etc.

Good Examples:

#1 Circular Dendrogram. Instead of using the traditional way (the distance) to indicate groupings and hierarchy, it uses different colors and shape sizes. Works well with the circular shape.

Phylogeny and tempo of diversification in the supperradiation of spiny-rayed fishes. Edited by David M.Hillis, University of Texas. A good example of using color, illustrations, and a better indication of hierarchy in a circular dendrogram. The dash circle at the center really helped.

Products of Slavery and Child Labour by Giulia De Amicis. A dendrogram of hierarchic dataset. A good example of dendrograms based on hierarchic datasets.

Bad Examples:

A standard dendrogram with scale on the side. Not very appealing to me in terms of design, but it shows hierarchic between clusters.

A phylogenetic tree of the bacterial domain. Some clusters are too small/narrow to be observed. The hierarchy is hard to tell.

Tree of Life (~3,000 species, based on rRNA sequences) by David M. Hillis, Derrick Zwickl, and Robin Gutell, University of Texas. An example of a visually appealing dendrogram that is relying on scientific dataset. However, it lacks color. Cannot tell the clusters with one sight when zoomed out.