Merge pull request #395 from tidymodels/0.1.6-release-candidate

0.1.6 release candidate

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tune
 Title: Tidy Tuning Tools
-Version: 0.1.5.9001
+Version: 0.1.6
 Authors@R: 
     c(person(given = "Max",
              family = "Kuhn",

NEWS.md

@@ -1,4 +1,4 @@
-# tune (development version)
+# tune 0.1.6
 
 * When using `load_pkgs()`, packages that use random numbers on start-up do not affect the state of the RNG. We also added more control of the RNGkind to make it consistent with the user's previous value (#389). 
 

R/merge.R

@@ -20,7 +20,7 @@
 #'
 #' pca_rec <-
 #'   recipe(mpg ~ ., data = mtcars) %>%
-#'   step_knnimpute(all_predictors(), neighbors = tune()) %>%
+#'   step_impute_knn(all_predictors(), neighbors = tune()) %>%
 #'   step_pca(all_predictors(), num_comp = tune())
 #'
 #' pca_grid <-

R/param_set.workflows.R

@@ -11,7 +11,7 @@
 #' library(recipes)
 #'
 #' recipe(mpg ~ ., data = mtcars) %>%
-#'   step_knnimpute(all_predictors(), neighbors = tune()) %>%
+#'   step_impute_knn(all_predictors(), neighbors = tune()) %>%
 #'   step_pca(all_predictors(), num_comp = tune()) %>%
 #'   dials::parameters()
 #'

R/tune_args.R

@@ -28,7 +28,7 @@
 #' library(recipes)
 #'
 #' recipe(mpg ~ ., data = mtcars) %>%
-#'   step_knnimpute(all_predictors(), neighbors = tune()) %>%
+#'   step_impute_knn(all_predictors(), neighbors = tune()) %>%
 #'   step_pca(all_predictors(), num_comp = tune()) %>%
 #'   tune_args()
 #'

tests/helper-objects.R

@@ -48,7 +48,7 @@ lm_model <-
 no_engine <- linear_reg()
 
 weird_annotation <-
-  boost_tree(mode = "regression", trees = tune("$^%&#!")) %>%
+  boost_tree(mode = "classification", trees = tune("$^%&#!")) %>%
   set_engine("C5.0", rules = TRUE, noGlobalPruning = TRUE)
 
 glmn <- linear_reg(penalty = tune(), mixture = tune()) %>% set_engine("glmnet")