#' Encode a given factor variable using deviation encoding
#'
#' @description Transforms the original design matrix using a deviation dummy 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 The deviation dummy variable encoding, with reference class level set to -1.
#' The reference class is always the last class observed.
#' @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_deviation(X = design_mat, fact = "factor_var", keep_factor = FALSE)
#'
encode_deviation <- function(X, fact, keep_factor = FALSE, encoding_only = FALSE){
X <- data.table::data.table(X)
if(is.numeric(fact)){
fact <- colnames(X)[fact]
}
factor_var <- levels(as.factor(unlist(X[, .SD, .SDcols = fact])))
reference <- rep(-1, (length(factor_var)-1))
dummies <- data.frame(rbind(reference, diag(length(factor_var)-1)))
colnames(dummies) <- paste( fact,"_",
factor_var[1:length(factor_var)-1],
"_deviate" , sep = "")
rownames(dummies) <- NULL
dummy_mat <- cbind(factor_var, dummies )
colnames(dummy_mat)[1] <- fact
if(encoding_only == TRUE){
if(keep_factor == FALSE){
return(dummy_mat[,-1])
}
else{
return(dummy_mat)
}
}
X <- X[dummy_mat, on = fact]
if(keep_factor == FALSE){
X[,(fact) := NULL]
}
return(X)
}
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