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#' @title Mean Square Error
#'
#' @description Mean Square Error.
#'
#' @param object An object of class \code{explainer} created with function
#' \code{\link[DALEX]{explain}} from the DALEX package.
#' @param data New data that will be used to calculate the score.
#' Pass \code{NULL} if you want to use \code{data} from \code{object}.
#' @param y New y parameter will be used to calculate score.
#' @param ... Other arguments dependent on the type of score.
#'
#' @return An object of class \code{auditor_score}.
#'
#' @examples
#' dragons <- DALEX::dragons[1:100, ]
#'
#' # fit a model
#' model_lm <- lm(life_length ~ ., data = dragons)
#'
#' lm_audit <- audit(model_lm, data = dragons, y = dragons$life_length)
#'
#' # calculate score
#' score_mse(lm_audit)
#'
#' @seealso \code{\link{score}}
#'
#' @export
score_mse <- function(object, data = NULL, y = NULL, ...) {
if(!("explainer" %in% class(object))) stop("The function requires an object created with explain() function from the DALEX package.")
# inject new data to the explainer
if (!is.null(data)){
object$data <- data
object$y <- y
object$y_hat <- object$predict_function(object$model, data)
}
mse_results <- list(
name = "mse",
score = mean((object$y - object$y_hat)^2)
)
class(mse_results) <- "auditor_score"
mse_results
}
#' @rdname score_mse
#' @export
scoreMSE<- function(object) {
warning("Please note that 'scoreMSE()' is now deprecated, it is better to use 'score_mse()' instead.")
score_mse(object)
}
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