pub fn gaussian_kernel(d: f64, h: f64) -> f64Expand description
Gaussian kernel: K(d, h) = exp(-d² / (2h²)).
This is the un-normalized version used by Nadaraya-Watson regression and kernel classification. For density estimation with normalization, see the smoothing module.