Hierarchical clustering is an unsupervised machine learning that identify closest cluster and group them together. Basic of Machine Learning article can be found here. Hierarchical clustering works with only 2 steps repeatedly. Firstly, detect 2 or more closest points or clusters. Secondly, group them together. The next steps are the iteration of the first two steps until all of the data points are grouped in clusters. The illustration below describes how hierarchical clustering groups data points and build dendrogram at the same time.
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Data Science and GIS 