RC 1.1.0 (#71)

* doc and version updates

* remove due to ranger

.github/workflows/R-CMD-check.yaml

@@ -31,7 +31,6 @@ jobs:
           - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
           - {os: ubuntu-latest,   r: 'release'}
           - {os: ubuntu-latest,   r: 'oldrel-1'}
-          - {os: ubuntu-latest,   r: 'oldrel-2'}
 
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}

DESCRIPTION

@@ -1,10 +1,10 @@
 Package: finetune
 Title: Additional Functions for Model Tuning
-Version: 1.0.1.9002
+Version: 1.1.0
 Authors@R: c(
     person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-2402-136X")),
-    person(given = "Posit Software, PBC", role = c("cph", "fnd"))
+    person("Posit Software, PBC", role = c("cph", "fnd"))
   )
 Description: The ability to tune models is important. 'finetune' enhances
     the 'tune' package by providing more specialized methods for finding
@@ -19,13 +19,13 @@ URL: https://github.com/tidymodels/finetune,
 BugReports: https://github.com/tidymodels/finetune/issues
 Depends: 
     R (>= 3.5),
-    tune (>= 1.0.1.9002)
+    tune (>= 1.1.1)
 Imports: 
     cli,
     dials (>= 0.1.0),
     dplyr (>= 1.1.1),
     ggplot2,
-    parsnip (>= 1.0.2),
+    parsnip (>= 1.1.0),
     purrr,
     rlang,
     tibble,
@@ -49,8 +49,6 @@ Suggests:
     spelling,
     testthat,
     yardstick
-Remotes:
-    tidymodels/tune
 Config/Needs/website: tidyverse/tidytemplate
 Config/testthat/edition: 3
 Encoding: UTF-8

NEWS.md

@@ -1,4 +1,6 @@
-# finetune (development version)
+# finetune 1.1.0
+
+* Various minor changes to keep up with developments in the tune and dplyr packages (#60) (#62) (#67) (#68). 
 
 * Corrects `.config` output with `save_pred = TRUE` in `tune_sim_anneal()`. The function previously outputted a constant `Model1_Preprocessor1` in the `.predictions` slot, and now provides `.config` values that align with those in `.metrics` (#57).
 

README.md

@@ -113,9 +113,7 @@ grid_anova <-
 #> ℹ Racing will maximize the roc_auc metric.
 #> ℹ Resamples are analyzed in a random order.
 #> ℹ Bootstrap10: 14 eliminated; 6 candidates remain.
-#> 
 #> ℹ Bootstrap04: 2 eliminated; 4 candidates remain.
-#> 
 #> ℹ Bootstrap03: All but one parameter combination were eliminated.
 
 show_best(grid_anova, metric = "roc_auc", n = 2)
@@ -136,17 +134,11 @@ grid_win_loss<-
 #> ℹ Racing will maximize the roc_auc metric.
 #> ℹ Resamples are analyzed in a random order.
 #> ℹ Bootstrap10: 3 eliminated; 17 candidates remain.
-#> 
 #> ℹ Bootstrap04: 2 eliminated; 15 candidates remain.
-#> 
 #> ℹ Bootstrap03: 2 eliminated; 13 candidates remain.
-#> 
 #> ℹ Bootstrap01: 1 eliminated; 12 candidates remain.
-#> 
 #> ℹ Bootstrap07: 1 eliminated; 11 candidates remain.
-#> 
 #> ℹ Bootstrap05: 1 eliminated; 10 candidates remain.
-#> 
 #> ℹ Bootstrap08: 1 eliminated; 9 candidates remain.
 
 show_best(grid_win_loss, metric = "roc_auc", n = 2)