export xgb_pred() (#688)

* export `xgb_pred()`

* rename function and arg

* update news

Author: hfrick

DESCRIPTION

@@ -89,4 +89,4 @@ Config/rcmdcheck/ignore-inconsequential-notes: true
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.1.2
+RoxygenNote: 7.1.2.9000

NAMESPACE

@@ -294,6 +294,7 @@ export(update_main_parameters)
 export(update_model_info_file)
 export(varying)
 export(varying_args)
+export(xgb_predict)
 export(xgb_train)
 importFrom(dplyr,arrange)
 importFrom(dplyr,bind_cols)

NEWS.md

@@ -1,12 +1,16 @@
 # parsnip (development version)
 
+* Exported `xgb_predict()` which wraps xgboost's `predict()` method for use with parsnip extension packages (#688).
+
+
 # parsnip 0.2.1
 
 * Fixed a major bug in spark models induced in the previous version (#671).
 
 * Updated the parsnip add-in with new models and engines. 
 
 * Updated parameter ranges for some `tunable()` methods and added a missing engine argument for brulee models. 
+
 * Added information about how to install the mixOmics package for PLS models (#680)
 
 

R/boost_tree.R

@@ -217,8 +217,8 @@ check_args.boost_tree <- function(object) {
 
 #' Boosted trees via xgboost
 #'
-#' `xgb_train` is a wrapper for `xgboost` tree-based models where all of the
-#'  model arguments are in the main function.
+#' `xgb_train()` and `xgb_predict()` are wrappers for `xgboost` tree-based
+#' models where all of the model arguments are in the main function.
 #'
 #' @param x A data frame or matrix of predictors
 #' @param y A vector (factor or numeric) or matrix (numeric) of outcome data.
@@ -251,7 +251,7 @@ check_args.boost_tree <- function(object) {
 #' @param event_level For binary classification, this is a single string of either
 #' `"first"` or `"second"` to pass along describing which level of the outcome
 #' should be considered the "event".
-#' @param ... Other options to pass to `xgb.train`.
+#' @param ... Other options to pass to `xgb.train()` or xgboost's method for `predict()`.
 #' @return A fitted `xgboost` object.
 #' @keywords internal
 #' @export
@@ -383,13 +383,17 @@ maybe_proportion <- function(x, nm) {
   }
 }
 
-xgb_pred <- function(object, newdata, ...) {
-  if (!inherits(newdata, "xgb.DMatrix")) {
-    newdata <- maybe_matrix(newdata)
-    newdata <- xgboost::xgb.DMatrix(data = newdata, missing = NA)
+#' @rdname xgb_train
+#' @param new_data A rectangular data object, such as a data frame.
+#' @keywords internal
+#' @export
+xgb_predict <- function(object, new_data, ...) {
+  if (!inherits(new_data, "xgb.DMatrix")) {
+    new_data <- maybe_matrix(new_data)
+    new_data <- xgboost::xgb.DMatrix(data = new_data, missing = NA)
   }
 
-  res <- predict(object, newdata, ...)
+  res <- predict(object, new_data, ...)
 
   x <- switch(
     object$params$objective,
@@ -482,9 +486,9 @@ multi_predict._xgb.Booster <-
   }
 
 xgb_by_tree <- function(tree, object, new_data, type, ...) {
-  pred <- xgb_pred(
+  pred <- xgb_predict(
     object$fit,
-    newdata = new_data,
+    new_data = new_data,
     iterationrange = c(1, tree + 1),
     ntreelimit = NULL
   )

R/boost_tree_data.R

@@ -108,8 +108,8 @@ set_pred(
   value = list(
     pre = NULL,
     post = NULL,
-    func = c(fun = "xgb_pred"),
-    args = list(object = quote(object$fit), newdata = quote(new_data))
+    func = c(fun = "xgb_predict"),
+    args = list(object = quote(object$fit), new_data = quote(new_data))
   )
 )
 
@@ -121,8 +121,8 @@ set_pred(
   value = list(
     pre = NULL,
     post = NULL,
-    func = c(fun = "xgb_pred"),
-    args = list(object = quote(object$fit), newdata = quote(new_data))
+    func = c(fun = "xgb_predict"),
+    args = list(object = quote(object$fit), new_data = quote(new_data))
   )
 )
 
@@ -170,8 +170,8 @@ set_pred(
       }
       x
     },
-    func = c(pkg = NULL, fun = "xgb_pred"),
-    args = list(object = quote(object$fit), newdata = quote(new_data))
+    func = c(pkg = NULL, fun = "xgb_predict"),
+    args = list(object = quote(object$fit), new_data = quote(new_data))
   )
 )
 
@@ -196,8 +196,8 @@ set_pred(
       colnames(x) <- object$lvl
       x
     },
-    func = c(pkg = NULL, fun = "xgb_pred"),
-    args = list(object = quote(object$fit), newdata = quote(new_data))
+    func = c(pkg = NULL, fun = "xgb_predict"),
+    args = list(object = quote(object$fit), new_data = quote(new_data))
   )
 )
 
@@ -209,8 +209,8 @@ set_pred(
   value = list(
     pre = NULL,
     post = NULL,
-    func = c(fun = "xgb_pred"),
-    args = list(object = quote(object$fit), newdata = quote(new_data))
+    func = c(fun = "xgb_predict"),
+    args = list(object = quote(object$fit), new_data = quote(new_data))
   )
 )