Preprocess data — preprocess

Preprocess data so they can be used as input for train_frm().

Usage

preprocess_data(
  data,
  degree_polynomial = 1,
  interaction_terms = FALSE,
  verbose = 1,
  nw = 1,
  rm_near_zero_var = TRUE,
  rm_na = TRUE
)

data: Dataframe with columns RT, NAME, SMILES
degree_polynomial: Defines how many polynomials get added (if 3 quadratic and cubic terms get added).
interaction_terms: If TRUE all interaction terms get added to data set.
verbose: 0 == no output, 1 == show progress, 2 == show progress and warnings
nw: number of workers to use for parallel processing
rm_near_zero_var: A logical value indicating whether to remove near zero variance predictors. Setting this to TRUE can cause the CV results to be overoptimistic, as the variance filtering is done on the whole dataset, i.e. information from the test folds is used for feature selection.
rm_na: A logical value indicating whether to remove NA values. Setting this to TRUE can cause the CV results to be overoptimistic, as the filtering is done on the whole dataset, i.e. information from the test folds is used for feature selection.

A dataframe with the preprocessed data

data <- head(RP, 3) # Only use first three rows to speed up example runtime
pre <- preprocess_data(data, verbose = 0)