buildTuningGrid() — buildTuningGrid • amRml

Builds a tuning grid according to the input model.

buildTuningGrid(
  model = "LR",
  penalty_vec = 10^seq(-4, -1, length.out = 10),
  mix_vec = 0:5/5
)

Arguments

model: rlang::chr Currently, logistic regression ("LR") is supported.
penalty_vec: pillar::num A vector containing penalty (regularization strength) values to try (for logistic regression). Recommended range: 10^-4 to 10^4.
mix_vec: pillar::num A vector containing mixture values to try for logistic regression. 0 corresponds to L2 regularization; 1 corresponds to L1; intermediate values (0, 1) correspond to elastic net.

A logistic regression tuning grid as a tibble