covariance function

A covariance function describes how two points in a dataset are related based on their positions or inputs. It measures whether values at similar points tend to be close or vary together, indicating their dependence. Think of it as a rule that tells us how strongly two observations are connected depending on their location in the input space. This is fundamental in models like Gaussian processes, where understanding these relationships helps predict unknown values based on observed data, capturing patterns and smoothness across the domain.