#' Helper function to fit a highly adaptive lasso to a fold as part of parallelized call
#' @name fit_hal_parallel
#' @param folds_df_list_fold
#' @param X_var Names of column corresponding covariates to use
#' @param n_pos_var Name of column corresponding to numbers positive
#' @param n_neg_var Name of column corresponding to numbers negative
fit_hal_parallel <- function(folds_df_list_fold,
X_var,
n_pos_var,
n_neg_var) {
X <- folds_df_list_fold$train[, X_var]
Y <- cbind(folds_df_list_fold$train[, n_neg_var],
folds_df_list_fold$train[, n_pos_var])
pred_data <- folds_df_list_fold$valid[, X_var]
hal_mod <- fit_hal(X, Y, family = "binomial", yolo = FALSE)
predict(hal_mod, new_data = pred_data)
}
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