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topepotopepo
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many more experts (even of specific S3 methods)
1 parent 8b73b3b commit 8920333

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-139
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‎NAMESPACE

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@@ -25,12 +25,18 @@ S3method(predict,model_spec)
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S3method(predict,nullmodel)
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S3method(predict_class,"_lognet")
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S3method(predict_class,"_multnet")
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S3method(predict_class,model_fit)
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S3method(predict_classprob,"_lognet")
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S3method(predict_classprob,"_multnet")
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S3method(predict_classprob,model_fit)
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S3method(predict_confint,model_fit)
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S3method(predict_numeric,"_elnet")
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S3method(predict_numeric,model_fit)
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S3method(predict_quantile,model_fit)
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S3method(predict_raw,"_elnet")
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S3method(predict_raw,"_lognet")
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S3method(predict_raw,"_multnet")
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S3method(predict_raw,model_fit)
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S3method(print,boost_tree)
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S3method(print,control_parsnip)
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S3method(print,decision_tree)
@@ -92,7 +98,9 @@ export(boost_tree)
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export(check_empty_ellipse)
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export(check_final_param)
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export(control_parsnip)
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export(convert_stan_interval)
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export(decision_tree)
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export(eval_args)
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export(fit)
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export(fit.model_spec)
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export(fit_control)
@@ -122,6 +130,13 @@ export(null_value)
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export(nullmodel)
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export(pred_value_template)
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export(predict.model_fit)
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export(predict_class.model_fit)
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export(predict_classprob.model_fit)
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export(predict_confint.model_fit)
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export(predict_numeric)
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export(predict_numeric.model_fit)
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export(predict_quantile.model_fit)
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export(predict_raw.model_fit)
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export(rand_forest)
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export(rpart_train)
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export(set_args)
@@ -144,6 +159,7 @@ export(svm_poly)
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export(svm_rbf)
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export(tidy.model_fit)
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export(translate)
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export(translate.default)
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export(update_dot_check)
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export(update_main_parameters)
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export(varying)

‎R/aaa.R

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@@ -13,7 +13,13 @@ maybe_multivariate <- function(results, object) {
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results
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}
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#' Convenience function for intervals
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#' @importFrom stats quantile
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#' @export
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#' @keywords internal
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#' @param x A fitted model object
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#' @param level Level of uncertainty for intervals
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#' @param lower Is `level` the lower level?
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convert_stan_interval <- function(x, level = 0.95, lower = TRUE) {
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alpha <- (1 - level) / 2
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if (!lower) {

‎R/arguments.R

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@@ -103,6 +103,11 @@ maybe_eval <- function(x) {
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y
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}
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#' Evaluate parsnip model arguments
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#' @export
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#' @keywords internal
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#' @param spec A model specification
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#' @param ... Not used.
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eval_args <- function(spec, ...) {
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spec$args <- purrr::map(spec$args, maybe_eval)
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spec$eng_args <- purrr::map(spec$eng_args, maybe_eval)

‎R/predict_class.R

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# Other predict methods.
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#
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# These are internal functions not meant to be directly called by the user.
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#
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# @keywords internal
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# @rdname other_predict
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# @inheritParams predict.model_fit
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# @method predict_class model_fit
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# @export predict_class.model_fit
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# @export
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#' Other predict methods.
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#'
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#' These are internal functions not meant to be directly called by the user.
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#'
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#' @keywords internal
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#' @rdname other_predict
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#' @inheritParams predict.model_fit
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#' @method predict_class model_fit
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#' @export predict_class.model_fit
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#' @export
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predict_class.model_fit <- function(object, new_data, ...) {
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if (object$spec$mode != "classification")
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rlang::abort("`predict.model_fit()` is for predicting factor outcomes.")

‎R/predict_classprob.R

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# @keywords internal
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# @rdname other_predict
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# @inheritParams predict.model_fit
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# @method predict_classprob model_fit
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# @export predict_classprob.model_fit
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# @export
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#' @keywords internal
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#' @rdname other_predict
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#' @inheritParams predict.model_fit
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#' @method predict_classprob model_fit
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#' @export predict_classprob.model_fit
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#' @export
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#' @importFrom tibble as_tibble is_tibble tibble
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predict_classprob.model_fit <- function(object, new_data, ...) {
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if (object$spec$mode != "classification")

‎R/predict_interval.R

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# @keywords internal
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# @rdname other_predict
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# @param level A single numeric value between zero and one for the
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# interval estimates.
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# @param std_error A single logical for wether the standard error should be
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# returned (assuming that the model can compute it).
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# @inheritParams predict.model_fit
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# @method predict_confint model_fit
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# @export predict_confint.model_fit
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# @export
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#' @keywords internal
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#' @rdname other_predict
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#' @param level A single numeric value between zero and one for the
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#' interval estimates.
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#' @param std_error A single logical for wether the standard error should be
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#' returned (assuming that the model can compute it).
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#' @inheritParams predict.model_fit
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#' @method predict_confint model_fit
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#' @export predict_confint.model_fit
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#' @export
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predict_confint.model_fit <- function(object, new_data, level = 0.95, std_error = FALSE, ...) {
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if (is.null(object$spec$method$pred$conf_int))

‎R/predict_numeric.R

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# @keywords internal
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# @rdname other_predict
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# @inheritParams predict.model_fit
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# @method predict_numeric model_fit
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# @export predict_numeric.model_fit
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# @export
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#' @keywords internal
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#' @rdname other_predict
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#' @inheritParams predict.model_fit
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#' @method predict_numeric model_fit
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#' @export predict_numeric.model_fit
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#' @export
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predict_numeric.model_fit <- function(object, new_data, ...) {
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if (object$spec$mode != "regression")
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rlang::abort(glue::glue("`predict_numeric()` is for predicting numeric outcomes. ",
@@ -45,9 +44,9 @@ predict_numeric.model_fit <- function(object, new_data, ...) {
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}
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# @export
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# @keywords internal
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# @rdname other_predict
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# @inheritParams predict_numeric.model_fit
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#' @export
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#' @keywords internal
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#' @rdname other_predict
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#' @inheritParams predict_numeric.model_fit
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predict_numeric <- function(object, ...)
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UseMethod("predict_numeric")

‎R/predict_quantile.R

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# @keywords internal
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# @rdname other_predict
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# @param quant A vector of numbers between 0 and 1 for the quantile being
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# predicted.
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# @inheritParams predict.model_fit
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# @method predict_quantile model_fit
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# @export predict_quantile.model_fit
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# @export
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#' @keywords internal
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#' @rdname other_predict
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#' @param quant A vector of numbers between 0 and 1 for the quantile being
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#' predicted.
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#' @inheritParams predict.model_fit
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#' @method predict_quantile model_fit
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#' @export predict_quantile.model_fit
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#' @export
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predict_quantile.model_fit <-
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function (object, new_data, quantile = (1:9)/10, ...) {
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function(object, new_data, quantile = (1:9)/10, ...) {
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if (is.null(object$spec$method$pred$quantile))
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rlang::abort("No quantile prediction method defined for this engine.")

‎R/predict_raw.R

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# @rdname predict.model_fit
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# @inheritParams predict.model_fit
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# @method predict_raw model_fit
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# @export predict_raw.model_fit
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# @export
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#' @rdname predict.model_fit
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#' @method predict_raw model_fit
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#' @export predict_raw.model_fit
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#' @export
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predict_raw.model_fit <- function(object, new_data, opts = list(), ...) {
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protected_args <- names(object$spec$method$pred$raw$args)
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dup_args <- names(opts) %in% protected_args

‎R/translate.R

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#' It translates generic parameters to their counterparts.
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#'
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#' @param x A model specification.
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#' @param engine The computational engine for the model (see `?set_engine`).
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#' @param ... Not currently used.
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#' @details
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#' `translate()` produces a _template_ call that lacks the specific
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#' @importFrom utils getFromNamespace
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#' @importFrom purrr list_modify
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#' @importFrom rlang lgl
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#' @rdname translate
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#' @export
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#' @export translate.default
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translate.default <- function(x, engine = x$engine, ...) {
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check_empty_ellipse(...)
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if (is.null(engine))

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