survsrf_tune: A repeated 3-fold CV over a hyperparameters grid

In survcompare: Nested Cross-Validation to Compare Cox-PH, Cox-Lasso, Survival Random Forests

A repeated 3-fold CV over a hyperparameters grid

Description

A repeated 3-fold CV over a hyperparameters grid

Usage

survsrf_tune(
  df_tune,
  predict.factors,
  repeat_tune = 1,
  fixed_time = NaN,
  tuningparams = list(),
  max_grid_size = 10,
  inner_cv = 3,
  randomseed = NaN
)

Arguments

df_tune	data
predict.factors	list of predictor names
repeat_tune	number of repeats
fixed_time	not used here, but for some models the time for which performance is optimized
tuningparams	if given, list of hyperparameters, list(mtry=c(), nodedepth=c(),nodesize=c()), otherwise a wide default grid is used
max_grid_size	number of random grid searches for model tuning
inner_cv	number of cross-validation folds for hyperparameter tuning
randomseed	to choose random subgroup of hyperparams

Value

output=list(cindex_ordered, bestparams)

survcompare documentation built on June 25, 2025, 5:09 p.m.