Median-distance heuristic for RBF kernel bandwidth

Returns the median pairwise Euclidean distance between rows of X, which is a standard data-driven starting point for the RBF kernel bandwidth (Schölkopf & Smola, 2002). Use the result to define a sensible rbf_sigma search range centred on this value via dials::rbf_sigma(range = c(log10(sigma / 10), log10(sigma * 10))).

Usage

sigma_heuristic(X, sample_size = 500L, seed = NULL)

Arguments

X: A numeric matrix or data frame of predictors (already preprocessed — centred, scaled, etc.).
sample_size: Integer. If nrow(X) > sample_size, a random subsample is used to avoid O(n²) memory cost on large datasets. Default 500L.
seed: Integer seed for the subsample. Default NULL. The caller's RNG stream is restored on exit, so passing seed makes the subsample reproducible without affecting the caller's subsequent random draws.

Value

A scalar numeric: the median pairwise Euclidean distance.

Examples

X <- matrix(rnorm(200), ncol = 4)
sigma_heuristic(X)
#> [1] 2.779273