Hierarchical Clustering Algorithm & Methods with Python In any clustering exercise, determining the number of clusters is a time-consuming process. Because the commercial side of the business is more concerned with extracting meaning from these groups, it’s crucial to visualize the clusters in two dimensions and see if they’re distinct. PCA or Factor Analysis can be used to achieve this goal. This is a common method for presenting final results to various stakeholders, making it easier for everyone to consume the output.
Now we look into examples using Python to demonstrate the Hierarchical Clustering Model