The Federalist Papers comprises of 85 articles written in the 1780s by founding fathers Alexander Hamilton, James Madison and John Jay. They wrote under a collective pseudonym, Publius, so keep their involvement secret. But who wrote what? There is much dispute. Let's try K-Means Clustering.
K-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells. For our example we’ll have 68 observations (papers) into 2 clusters (2 authors, Madison and Hamilton).
Once the data has been converted into workable features, we can fit them onto a 2-cluster model. This is unsupervised - we are effectively just pouring in our (ideally) significant data and telling it that there are two distinct sets within it, and to try and extricate them.
Spoiler: most of them were by Hamilton.
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