survcompare (version 0.2.0)

survsrf_tune: 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
)

Value

output=list(cindex_ordered, bestparams)

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