A dendrogram is a tree data structure that allows us to represent the entire clustering hierarchy produced by either an agglomerative or divisive algorithm. The idea is to put the samples on the x axis and the dissimilarity level on the y axis. Whenever two clusters are merged, the dendrogram shows a connection corresponding to the dissimilarity level at which it occurred. Hence, in an agglomerative scenario, a dendrogram always starts with all samples considered as clusters and moves upward (the direction is purely conventional) until a single cluster is defined.
For didactic purposes, it's preferable to show the dendrogram corresponding to a very small dataset, X, but all the concepts that we are going to discuss can be applied to any situation. However, with larger datasets, it will often be necessary to apply some truncations in order to visualize...
