How to compare Dendrograms in R

Dendrograms are tree-like structures that are used to represent the results of hierarchical clustering. Comparing dendrograms can be useful for understanding the similarities and differences between different clustering solutions, or for comparing the results of different linkage methods or distance metrics.

In R, dendrograms can be compared using the “cophenetic()” and “cor.dendrogram()” functions from the “ape” package. The “cophenetic()” function takes a dendrogram object as input and returns a matrix that contains the cophenetic distances between all pairs of observations. The “cor.dendrogram()” function takes two dendrogram objects as input and returns a correlation coefficient that measures the similarity between the two dendrograms.

Another way to compare dendrograms is by visualizing them side-by-side using the “grid.arrange()” function from the “gridExtra” package. This function takes a list of plots as input and arranges them in a grid. By passing in multiple dendrogram plots, they can be viewed side-by-side for comparison.

Another way to compare dendrograms is by using the package “dendextend” which provide several functions to compare dendrograms such as “cophenetic()”, “cor()”, “dendlist.cor()” and more. These functions are similar to the ones in the “ape” package, but with more flexibility.

In summary, comparing dendrograms can be useful for understanding the similarities and differences between different clustering solutions. In R, dendrograms can be compared using the “cophenetic()” and “cor.dendrogram()” functions from the “ape” package which return a matrix and correlation coefficient respectively. Another way to compare dendrograms is by visualizing them side-by-side using the “grid.arrange()” function from the “gridExtra” package. The package “dendextend” also provide several functions to compare dendrograms, with more flexibility than the “ape” package.

In this Applied Machine Learning Recipe, the reader will learn: How to compare Dendrograms in R.