How to visualise Hierarchical Clustering (agglomerative) in R

Hierarchical Clustering is a type of cluster analysis that creates a tree-like structure called a dendrogram to represent the different clusters. There are two main types of hierarchical clustering: agglomerative and divisive. Agglomerative hierarchical clustering is a bottom-up approach that starts with each data point as its own cluster, and then combines them into successively larger clusters. The process continues until all data points are in a single cluster or a user-defined number of clusters is reached.

In R, agglomerative hierarchical clustering can be visualized using the “ggdendro” package. This package provides a set of functions that can be used to create dendrograms and heatmaps from the cluster results. The “ggdendro” package provides a function called “ggdendrogram()” that can be used to create a dendrogram from the results of the hierarchical clustering. The function takes the results of the clustering as input and returns a dendrogram that can be customized with various options such as color and shape of the branches, labels and more.

Another way to visualize the results of agglomerative hierarchical clustering is by using heatmaps. A heatmap is a graphical representation of data where individual values are represented as colors. The “ggheatmap” function from the “ggdendro” package can be used to create a heatmap from the results of the hierarchical clustering. The function takes the results of the clustering as input, and returns a heatmap that can be customized with various options such as color schemes, labels and more.

In summary, hierarchical clustering is a type of cluster analysis that creates a tree-like structure called a dendrogram to represent the different clusters. Agglomerative hierarchical clustering is a bottom-up approach that starts with each data point as its own cluster, and then combines them into successively larger clusters. In R, this process can be visualized using the “ggdendro” package which provides a set of functions that can be used to create dendrograms and heatmaps from the cluster results. The “ggdendro” package provides a function called “ggdendrogram()” that can be used to create a dendrogram from the results of the hierarchical clustering. Another way to visualize the results of agglomerative hierarchical clustering is by using heatmaps, this can be done by using the “ggheatmap” function from the “ggdendro” package.

In this Applied Machine Learning Recipe, you will learn: How to visualise Hierarchical Clustering (agglomerative) in R.