Project 2: Kernel Regression Models
Kernel regression is a non-parametric technique that is useful when the distribution of the observed data is unknown. In this project, I wrote two univariate kernel regression models: Gaussian Kernel and Epanechnikov Kernel. The two models were compared to a multi-dimensional Kernel in terms of prediction accuracy.
