models_pro: Run Multiple Prognostic Models

In E2E: Ensemble Learning Framework for Diagnostic and Prognostic Modeling

Run Multiple Prognostic Models

Description

Trains and evaluates one or more registered prognostic models on a given dataset.

Usage

models_pro(
  data,
  model = "all_pro",
  tune = FALSE,
  seed = 123,
  time_unit = "day",
  years_to_evaluate = c(1, 3, 5)
)

Arguments

data	A data frame for training. The first column must be the sample ID, the second column the event status (0/1), the third column the time, and subsequent columns the features.
model	A character string or vector of character strings, specifying which models to run. Use "all_pro" to run all registered models.
tune	Logical, whether to enable hyperparameter tuning for individual models.
seed	An integer, for reproducibility of random processes.
time_unit	A character string, the unit of time in the third column of data. Can be "day", "month", or "year".
years_to_evaluate	A numeric vector of specific years at which to calculate time-dependent AUROC.

Value

A named list, where each element corresponds to a run model and contains its trained model_object, sample_score data frame, and evaluation_metrics.

See Also

initialize_modeling_system_pro, evaluate_model_pro

Examples

# NOTE: This example requires the 'train_pro' dataset to be exported by the package.
# If it is not, replace `data(train_pro)` with code to create a dummy dataframe.
# For demonstration, we assume `train_pro` is available.
if (requireNamespace("E2E", quietly = TRUE) &&
 "train_pro" %in% utils::data(package = "E2E")$results[,3]) {
  data(train_pro, package = "E2E")

  # Initialize the modeling system
  initialize_modeling_system_pro()

  # Run selected models
  results <- models_pro(
    data = train_pro,
    model = c("lasso_pro", "rsf_pro"), # Run only Lasso and RSF
    years_to_evaluate = c(1, 3, 5),
    seed = 42
  )

  # Print summaries
  for (model_name in names(results)) {
    print_model_summary_pro(model_name, results[[model_name]])
  }
}

E2E documentation built on Aug. 27, 2025, 1:09 a.m.