removed S3 classes to create models for issue #2

Author: topepo

NAMESPACE

@@ -3,10 +3,8 @@
 S3method(finalize,logistic_reg)
 S3method(finalize,rand_forest)
 S3method(fit,model_spec)
-S3method(logistic_reg,default)
 S3method(print,logistic_reg)
 S3method(print,rand_forest)
-S3method(rand_forest,default)
 S3method(update,logistic_reg)
 S3method(update,rand_forest)
 export(finalize)

R/logistic_reg.R

@@ -27,22 +27,6 @@
 #' \item \pkg{Stan}:  `"rstanarm"` 
 #' \item \pkg{Spark}: `"spark"`
 #' }
-#' @export
-#' @rdname logistic_reg
-#' @importFrom rlang expr enquo missing_arg
-#' @importFrom purrr map_lgl
-#' @seealso [varying()], [fit()]
-#' @examples 
-#' logistic_reg()
-#' 
-#' # Parameters can be represented by a placeholder:
-#' logistic_reg(regularization = varying())
-
-logistic_reg <- function (mode, ...)
-  UseMethod("logistic_reg")
-
-#' @rdname logistic_reg
-#' @export
 #' @param mode A single character string for the type of model.
 #'  The only possible value for this model is "classification".
 #' @param engine_args A named list of arguments to be used by the
@@ -58,9 +42,17 @@ logistic_reg <- function (mode, ...)
 #'  (the lasso).
 #' @param ... Used for S3 method consistency. Any arguments passed to
 #'  the ellipses will result in an error. Use `engine_args` instead.
+#' @seealso [varying()], [fit()]
+#' @examples 
+#' logistic_reg()
+#' 
+#' # Parameters can be represented by a placeholder:
+#' logistic_reg(regularization = varying())
+#' @export
 
-
-logistic_reg.default <-
+#' @importFrom rlang expr enquo missing_arg
+#' @importFrom purrr map_lgl
+logistic_reg <-
   function(mode = "classification",
            regularization = NULL,
            mixture = NULL,

R/rand_forest.R

@@ -26,28 +26,12 @@
 #'  to determine the _mode_ of the model. For `rand_forest`, the
 #'  possible modes are "regression" and "classification".
 #' 
-#'   The model can be created using the [fit()] function using the
+#' The model can be created using the [fit()] function using the
 #'  following _engines_:
 #' \itemize{
 #' \item \pkg{R}:  `"ranger"` or `"randomForests"` 
 #' \item \pkg{Spark}: `"spark"`
 #' }
-#' @export
-#' @rdname rand_forest
-#' @importFrom rlang expr enquo missing_arg
-#' @importFrom purrr map_lgl
-#' @seealso [varying()], [fit()]
-#' @examples 
-#' rand_forest(mode = "classification", trees = 2000)
-#' 
-#' # Parameters can be represented by a placeholder:
-#' rand_forest(mode = "regression", mtry = varying())
-
-rand_forest <- function (mode, ...)
-  UseMethod("rand_forest")
-
-#' @rdname rand_forest
-#' @export
 #' @param mode A single character string for the type of model.
 #'  Possible values for this model are "unknown", "regression", or
 #'  "classification".
@@ -64,8 +48,17 @@ rand_forest <- function (mode, ...)
 #'  in a node that are required for the node to be split further.
 #' @param ... Used for method consistency. Any arguments passed to
 #'  the ellipses will result in an error. Use `engine_args` instead.
+#' @importFrom rlang expr enquo missing_arg
+#' @importFrom purrr map_lgl
+#' @seealso [varying()], [fit()]
+#' @examples 
+#' rand_forest(mode = "classification", trees = 2000)
+#' 
+#' # Parameters can be represented by a placeholder:
+#' rand_forest(mode = "regression", mtry = varying())
+#' @export
 
-rand_forest.default <-
+rand_forest <-
   function(mode = "unknown",
            mtry = NULL, trees = NULL, min_n = NULL,
            engine_args = list(), 

docs/articles/parsnip_Intro.html

@@ -74,7 +74,7 @@ Commonly used arguments to the modeling functions have their parameters exposed
 The arguments to the default function are:
 
 ```{r rf-def}
-args(parsnip:::rand_forest.default)
+args(rand_forest)
 ```
 
 However, there might be other arguments that you would like to change or allow to vary. These are accessible using the `engine_args` option. This is a named list of arguments in the form of the underlying function being called. For example, `ranger` has an option to set the internal random number seed. To set this to a specific value: