There are many occasions in which one might want to know the distance or similarity between two things, for which the means of calculating that distance is not necessarily clear. The distance between two points in Euclidean space is generally straightforward, but what about the distance between the top of Mount Everest to the bottom of the ocean? What about the distance between two sentences?
This mini-episode summarizes some of the considerations and a few of the means of calculating distance. We touch on Jaccard Similarity, Manhattan Distance, and a few others.
Thanks to listener Matt T for writing in and pointing out that our k-Nearest Neighbors episode mentioned uses in higher dimensional spaces without warning for how this particular algorithm suffers from the curse of dimensionality. Matt also suggested a great talk by Trevor Hastie which can be found here.