Introduction
I have a friend who is a city planner. One day, he was tasked with reassessing the location suitability of thousands of gas stations in the city, needing to find the positions of the k-nearest gas stations to each one.
How can we find the nearest k stations with little time? This is a practical application scenario of the k-nearest neighbors problem.
As such, he came to me for help, hoping I could provide a high-performance solution.
So I write down this article and which will guide you on efficiently solving the k-nearest neighbors problem using NumPy. By comparing it with a Python iterative solution, we will demonstrate the powerful performance of NumPy.