R/internal_evaluate_predictions.R

In cvms: Cross-Validation for Model Selection

# Evaluates single model object
# and extracts information like coefficients
internal_evaluate_predictions <- function(data,
                                          prediction_col,
                                          target_col,
                                          model_was_null_col,
                                          type,
                                          fold_info_cols = list(
                                            rel_fold = "rel_fold",
                                            abs_fold = "abs_fold",
                                            fold_column = "fold_column"
                                          ),
                                          fold_and_fold_col = NULL,
                                          group_info = NULL,
                                          model_specifics,
                                          metrics,
                                          id_col = NULL,
                                          id_method = NULL,
                                          stds_col = NULL,
                                          include_fold_columns = TRUE,
                                          include_predictions = TRUE,
                                          na.rm = dplyr::case_when(
                                            type == "gaussian" ~ TRUE,
                                            type == "binomial" ~ FALSE,
                                            type == "multinomial" ~ FALSE
                                          )) {

  if (type == "gaussian") {
    eval_pred_fn <- evaluate_predictions_gaussian
  } else if (type == "binomial") {
    eval_pred_fn <- evaluate_predictions_binomial
  } else if (type == "multinomial") {
    eval_pred_fn <- evaluate_predictions_multinomial
  }

  eval_pred_fn(
    data = data,
    prediction_col = prediction_col,
    target_col = target_col,
    model_was_null_col = model_was_null_col,
    id_col = id_col,
    id_method = id_method,
    fold_info_cols = fold_info_cols,
    fold_and_fold_col = fold_and_fold_col,
    group_info = group_info,
    stds_col = stds_col,
    model_specifics = model_specifics,
    metrics = metrics,
    include_fold_columns = include_fold_columns,
    include_predictions = include_predictions,
    na.rm = na.rm
  )
}