create recipe from data

Usage

prepare_ml_recipe(
  data,
  custom_recipe = NULL,
  corr_method = "spearman",
  corr_use = "pairwise.complete.obs",
  thres_list = NULL,
  step_list = NULL,
  vars_imp_ignore = c(".trt"),
  vars_fct_expl_na = NULL,
  vars_keep_corr = NULL,
  vars_no_trafo = NULL,
  one_hot,
  log_base
)

Arguments

data: raw data set to create recipe for
custom_recipe: if NULL, recipe will be created
corr_method, corr_use: defaulting to corr_method spearman and corr_use pairwise.complete.obs
thres_list, step_list: named list objects collecting all threshold values and step selection info, resp. Please refer to the documentation of the thres_* and prep_step_* arguments in prepare_ml() for detailed documentation and list entry names.
vars_imp_ignore: variables that shall not be imputed can be specified in vars_imp_ignore (vector of column names, defaults to vars_imp_ignore = '.trt'). Observations with missing values in these variables will be removed. Removal is documented in removed$rows.
vars_fct_expl_na: column names of factors for which NAs should be treated as an explicit factor level. Defaults to NULL.
vars_keep_corr: choose these variables over other options when removing variables due to high correlation in recipes::step_corr(). See recipes::step_rm() below for details.
vars_no_trafo: character vector defining variables that should be excluded from transformation steps such as log transformation and/or normalization (if applicable). Defaults to NULL.
one_hot: boolean. passed to recipes::step_dummy() to choose one hot encoding over dummy encoding
log_base: base to use for log-transformation in recipes::step_log(). Defaults to exp(1).

Value

a named list with entries containing

the unprepared recipe
the prepared recipe
info on steps included in the recipe
a list of relevant variables
a list of thresholds used
high_corr a tibble listing correlations above thres_corr. NULL if step_list$prep_step_corr = FALSE.

create recipe from data

Usage

Arguments

Value

See also