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RC 1.2.0 #109

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Mar 21, 2024
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RC 1.2.0 #109

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version and doc updates
Mar 21, 2024
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Mar 21, 2024
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1 change: 1 addition & 0 deletions .Rbuildignore
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^\.github$
^docs$
^pkgdown$
^revdep
1 change: 1 addition & 0 deletions .gitignore
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.Ruserdata
.DS_Store
docs
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Package: finetune
Title: Additional Functions for Model Tuning
Version: 1.1.0.9006
Version: 1.2.0
Authors@R: c(
person("Max", "Kuhn", , "[email protected]", role = c("aut", "cre"),
comment = c(ORCID = "0000-0003-2402-136X")),
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14 changes: 10 additions & 4 deletions NEWS.md
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# finetune (development version)
# finetune 1.2.0

* Improved error message from `tune_sim_anneal()` when values in the supplied `param_info` do not encompass all values evaluated in the `initial` grid. This most often happens when a user mistakenly supplies different parameter sets to the function that generated the initial results and `tune_sim_anneal()`.
## New Features

* Fixed bug where `tune_sim_anneal()` would fail when supplied parameters needing finalization. The function will now finalize needed parameter ranges internally (#39).
* finetune now fully supports models in the "censored regression" mode. These models can be fit, tuned, and evaluated like the regression and classification modes. [tidymodels.org](https://www.tidymodels.org/learn/#category=survival%20analysis) has more information and tutorials on how to work with survival analysis models.

* Fixed bug where packages specified in `control_race(pkgs)` were not actually loaded in `tune_race_anova()` (#74).
* Improved error message from `tune_sim_anneal()` when values in the supplied `param_info` do not encompass all values evaluated in the `initial` grid. This most often happens when a user mistakenly supplies different parameter sets to the function that generated the initial results and `tune_sim_anneal()`.

* `autoplot()` methods for racing objects will now use integers in x-axis breaks (#75).

* Enabling the `verbose_elim` control option for `tune_race_anova()` will now additionally introduce a message confirming that the function is evaluating against the burn-in resamples.

* Updates based on the new version of tune, primarily for survival analysis models (#104).

## Bug Fixes

* Fixed bug where `tune_sim_anneal()` would fail when supplied parameters needing finalization. The function will now finalize needed parameter ranges internally (#39).

* Fixed bug where packages specified in `control_race(pkgs)` were not actually loaded in `tune_race_anova()` (#74).

## Breaking Change

* Ellipses (...) are now used consistently in the package to require optional arguments to be named. `collect_predictions()`, `collect_metrics()` and `show_best()` methods previously had ellipses at the end of the function signature that have been moved to follow the last argument without a default value. Optional arguments previously passed by position will now error informatively prompting them to be named (#105).
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2 changes: 1 addition & 1 deletion README.Rmd
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Expand Up @@ -111,7 +111,7 @@ show_best(grid_win_loss, metric = "roc_auc", n = 2)

This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on Posit Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).
- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on Posit Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).

- If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/usemodels/issues).

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11 changes: 10 additions & 1 deletion README.md
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Expand Up @@ -110,10 +110,13 @@ set.seed(4)
grid_anova <-
rda_spec %>%
tune_race_anova(Class ~ ., resamples = rs, grid = grid, control = ctrl)
#> ℹ Evaluating against the initial 3 burn-in resamples.
#> 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)
Expand All @@ -134,11 +137,17 @@ 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)
Expand All @@ -157,7 +166,7 @@ By contributing to this project, you agree to abide by its terms.

- For questions and discussions about tidymodels packages, modeling, and
machine learning, please [post on Posit
Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).
Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).

- If you think you have encountered a bug, please [submit an
issue](https://github.com/tidymodels/usemodels/issues).
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