I have taken a problem statement of an NGO wanting to find the top 5-10 countries from a list of 169 who are in dire need of aid, in the article: K-Means Clustering Through an Example. Today I would like to solve the same problem using hierarchical clustering. Just to reiterate the problem statement, an NGO that is committed to fighting poverty in backward countries by providing basic amenities and relief during disasters and natural calamities has got a round of funding. It

We have seen in the previous post about Hierarchical Clustering, when it is used and why. We glossed over the criteria for creating clusters through dissimilarity measure which is typically the Euclidean distance between points. There are other distances that can be used like Manhattan and Minkowski too while Euclidean is the one most often used. There was a mention of "Single Linkages" too. The concept of linkage comes when you have more than 1 point in a cluster and the dis