Kernel regression

Kernel regression is a statistical method used to estimate the relationship between variables by giving more importance to data points near the point of interest. Imagine trying to predict the value at a specific point based on nearby data; the kernel function assigns weights that highlight closer points and diminish the influence of farther ones. This approach creates a smooth curve fitting the data without assuming a strict formula, making it flexible for capturing complex patterns. It's widely used in fields like machine learning and data analysis for its ability to adapt to various data shapes.