#' Encode a given factor variable using a multinomial logit representation
#'
#' @description Transforms the original design matrix using a mnl 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' - mnl.
#' @importFrom data.table data.table
#' @importFrom data.table setkeyv
#' @importFrom data.table .SD
#' @importFrom data.table ':='
#' @importFrom glmnet glmnet
#' @importFrom stats formula
#' @importFrom stats coef
#' @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_mnl(X = design_mat, fact = "factor_var", keep_factor = FALSE)
#'
encode_mnl <-
function(X,
fact,
keep_factor = FALSE,
encoding_only = FALSE) {
if (is.numeric(fact)) {
fact <- colnames(X)[fact]
}
X <- data.table::data.table(X)
mnl <- glmnet::glmnet(x = as.matrix(X[, .SD, .SDcols = -fact]),
y = unlist(X[, .SD, .SDcols = fact]),
family = "multinomial")
mnl <- coef(mnl, s = min(mnl$lambda), na.rm = TRUE)
mnl <- t(as.matrix(as.data.frame(lapply(mnl, as.matrix))))
mnl <- apply(mnl, MARGIN = 2, FUN = as.numeric)
mnl <- data.table::data.table(mnl)
colnames(mnl) <- paste(fact, "_",
c("intercept",
(1:(ncol(
mnl
) - 1))),
"_mnl", sep = "")
factor_var <- levels(as.factor(unlist(X[, .SD, .SDcols = fact])))
mnl <- cbind(factor_var, mnl)
colnames(mnl)[1] <- fact
mnl <- data.table::data.table(mnl)
if (encoding_only == TRUE) {
if (keep_factor == FALSE) {
return(mnl[, -1])
}
else{
return(mnl)
}
}
X <- X[mnl, on = fact]
if (keep_factor == FALSE) {
X[, (fact) := NULL]
}
return(X)
}
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