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#' @rdname predict.vlmc
#' @export
#' @examples
#' ## C++ backend
#' pc <- powerconsumption[powerconsumption$week == 5, ]
#' dts <- cut(pc$active_power, breaks = c(0, quantile(pc$active_power, probs = c(0.25, 0.5, 0.75, 1))))
#' model <- vlmc(dts, min_size = 5, backend = "C++")
#' predict(model, dts[1:5])
#' predict(model, dts[1:5], "probs")
predict.vlmc_cpp <- function(object, newdata, type = c("raw", "probs"),
final_pred = TRUE, ...) {
restore_model(object)
type <- match.arg(type)
assertthat::assert_that(rlang::is_logical(final_pred))
if (!missing(newdata) && !is.null(newdata)) {
assertthat::assert_that((typeof(newdata) == typeof(object$vals)) && (class(newdata) == class(object$vals)),
msg = "newdata is not compatible with the model state space"
)
dts <- to_dts(newdata, object$vals)
} else {
stop("newdata must be provided.")
}
if (type == "raw") {
object$vals[1 + object$root$predict_raw(dts$ix, final_pred)]
} else {
pre_res <- object$root$predict_probs(dts$ix, final_pred)
colnames(pre_res) <- as.character(object$vals)
pre_res
}
}
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