R/encode_mean.R

In JSzitas/categoryEncodings: Category Variable Encodings

#' Encode a given factor variable using means encoding
#'
#' @description Transforms the original design matrix using a means encoding.
#'
#' @param X The data.frame/data.table to transform.
#' @param fact The factor variable to encode by - either a positive integer specifying the
#'             column number, or the name of the column.
#' @param keep_factor Whether to keep the original factor column(defaults to **FALSE**).
#' @param encoding_only Whether to return the full transformed dataset or only the new
#'                      columns. Defaults to FALSE and returns the full dataset.
#'
#' @return A new data.table X which contains the new columns and optionally the old factor.
#' @details Uses the method from Johannemann et al.(2019)
#' 'Sufficient Representations for Categorical Variables' - Means Encoding.
#' @importFrom data.table data.table
#' @importFrom data.table setkeyv
#' @importFrom data.table .SD
#' @importFrom data.table ':='
#' @export
#'
#' @examples
#'
#' design_mat <- cbind( data.frame( matrix(rnorm(5*100),ncol = 5) ),
#'                      sample( sample(letters, 10), 100, replace = TRUE)
#'                      )
#' colnames(design_mat)[6] <- "factor_var"
#'
#' encode_mean(X = design_mat, fact = "factor_var", keep_factor = FALSE)
#'
encode_mean <-
  function(X,
           fact,
           keep_factor = FALSE,
           encoding_only = FALSE) {
    if (is.numeric(fact)) {
      fact <- colnames(X)[fact]
    }
    X <- data.table::data.table(X)
    data.table::setkeyv(X, fact)
    
    
    means <- X[, lapply(.SD, mean, na.rm = TRUE), by = fact]
    
    sel_vec <- which(colnames(X) == fact)
    
    colnames(means) <- c(fact,
                         paste(fact, "_",
                               colnames(X)[-sel_vec],
                               "_mean", sep = ""))
    
    if (encoding_only == TRUE) {
      if (keep_factor == FALSE) {
        return(means[,-1])
      }
      else{
        return(means)
      }
    }
    
    X <- X[means, on = fact]
    
    if (keep_factor == FALSE) {
      X[, (fact) := NULL]
    }
    return(X)
}