In statistics, the distance between vectors or data sets are computed in various ways depending on the problem statement and the properties of the data. These distances are often used in algorithms and techniques such as recommender systems, which help e-commerce companies such as Amazon, eBay, and so on, to recommend relevant products to the customers.
To get ready, the Distances library has to be installed and imported. We install it using the Pkg.add() function. It can be done as follows:
Pkg.add("Distances")
Then, the package has to be imported for use in the session. It can be imported through the
using ... command. This can be done as follows:
using Distances
Firstly, we will look at the Euclidean distance. It is the ordinary distance between two points in Euclidean space. This can be calculated through the Pythagorean distance calculation method, which is the square root of the square of the element-wise differences. This can be done using the...
