R/calc_confusion_matrix.R

In CDU-data-science-team/experienceAnalysis: Helper Functions for Text Mining

#' Calculate the confusion matrix
#'
#' Calculates the confusion matrix of observed and predicted classes, after
#' converting them into factors first (not currently done by
#' `conf_mat{yardstick}`).
#'
#' @param x A data frame with two columns: the column with the actual classes;
#'     and the column with the predicted classes. Any other columns will be
#'     ignored.
#' @param target_col_name A string with the column name of the target variable.
#' @param target_pred_col_name A string with the column name of the predictions
#'     for the target variable.
#' @param ... Further arguments passed from other methods.
#'
#' @return An object with class `conf_mat()` (see `conf_mat{yardstick}`).
#' @export
#'
#' @examples
#' library(experienceAnalysis)
#' mtcars %>%
#'   dplyr::mutate(carb_pred = sample(carb, size = nrow(.))) %>%  # Mock predictions column
#'   calc_accuracy_per_class(
#'     target_col_name = "carb",
#'     target_pred_col_name = "carb_pred"
#'   )
#'
#' # Custom column names
#' mtcars %>%
#'   dplyr::mutate(carb_pred = sample(carb, size = nrow(.))) %>%  # Mock predictions column
#'   calc_confusion_matrix(
#'     target_col_name = "carb",
#'     target_pred_col_name = "carb_pred"
#'   )

calc_confusion_matrix <- function(x, target_col_name, target_pred_col_name,
                                  ...) {

  # Convert cols to factors
  aux <- x %>%
    dplyr::select(dplyr::all_of(c(target_col_name, target_pred_col_name))) %>%
    dplyr::mutate(
      dplyr::across(
        dplyr::everything(),
        ~ as.factor(.)
      )
    )

  cm <- aux %>%
    yardstick::conf_mat(., {{target_col_name}}, {{target_pred_col_name}}, ...)

  return(cm)
}