tune v0.1.2
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Tidy Tuning Tools
The ability to tune models is important. 'tune' contains functions and
classes to be used in conjunction with other 'tidymodels' packages for
finding reasonable values of hyper-parameters in models, pre-processing
methods, and post-processing steps.
Readme
tune 
Overview
The goal of tune is to facilitate hyperparameter tuning for the tidymodels packages. It relies heavily on recipes, parsnip, and dials.
Installation
Install from CRAN:
install.packages("tune", repos = "http://cran.r-project.org") #or your local mirror
or you can install the current development version using:
devtools::install_github("tidymodels/tune")
Examples
There are several package vignettes, as well as articles available at tidymodels.org, demonstrating how to use tune.
Good places to begin include:
More advanced resources available are:
- Basic grid search for an SVM model
- Iterative Bayesian optimization of a classification model
- Advanced text mining example
- Notes on optimizations and parallel processing
- Details on acquisition function for scoring parameter combinations
Contributing
This project is released with a Contributor Code of Conduct. 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 RStudio Community.
If you think you have encountered a bug, please submit an issue.
Either way, learn how to create and share a reprex (a minimal, reproducible example), to clearly communicate about your code.
Check out further details on contributing guidelines for tidymodels packages and how to get help.
Functions in tune
| Name | Description | |
| control_bayes | Control aspects of the Bayesian search process | |
| autoplot.tune_results | Plot tuning search results | |
| coord_obs_pred | Use same scale for plots of observed vs predicted values | |
| augment.tune_results | Augment data with holdout predictions | |
| collect_predictions | Obtain and format results produced by tuning functions | |
| example_ames_knn | Example Analysis of Ames Housing Data | |
| check_rset | Get colors for tune text. | |
| expo_decay | Exponential decay function | |
| finalize_model | Splice final parameters into objects | |
| extract_recipe | Convenience functions to extract model or recipe | |
| filter_parameters | Remove some tuning parameter results | |
| min_grid.model_spec | Determine the minimum set of model fits | |
| outcome_names | Determine names of the outcome data in a workflow | |
| tune | A placeholder function for argument values that are to be tuned. | |
| fit_resamples | Fit multiple models via resampling | |
| .get_tune_parameters | Various accessor functions | |
| conf_mat_resampled | Compute average confusion matrix across resamples | |
| last_fit | Fit the final best model to the training set and evaluate the test set | |
| control_grid | Control aspects of the grid search process | |
| merge.recipe | Merge parameter grid values into objects | |
| message_wrap | Write a message that respects the line width | |
| reexports | Objects exported from other packages | |
| required_pkgs.model_spec | Determine packages required by objects | |
| load_pkgs | Quietly load package namespace | |
| tune_grid | Model tuning via grid search | |
| show_best | Investigate best tuning parameters | |
| tunable.model_spec | Find recommended methods for generating parameter values | |
| tune_bayes | Bayesian optimization of model parameters. | |
| tune_args | Determine arguments tagged for tuning | |
| parameters.workflow | Determination of parameter sets for other objects | |
| prob_improve | Acquisition function for scoring parameter combinations | |
| No Results! | ||
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Details
| License | MIT + file LICENSE |
| URL | https://github.com/tidymodels/tune, https://tune.tidymodels.org |
| Encoding | UTF-8 |
| LazyData | true |
| RoxygenNote | 7.1.1.9000 |
| Language | en-US |
| NeedsCompilation | no |
| Packaged | 2020-11-15 18:15:53 UTC; max |
| Repository | CRAN |
| Date/Publication | 2020-11-17 08:40:02 UTC |
| imports | cli (>= 2.0.0) , dials (>= 0.0.9) , dplyr (>= 1.0.0) , foreach , generics (>= 0.1.0) , ggplot2 , glue , GPfit , hardhat (>= 0.1.5) , parsnip (>= 0.1.4) , purrr (>= 0.3.2) , recipes (>= 0.1.15) , rlang (>= 0.4.0) , rsample (>= 0.0.8) , tibble (>= 2.1.3) , tidyr , utils , vctrs (>= 0.3.0) , workflows (>= 0.2.1) , yardstick (>= 0.0.7) |
| suggests | covr , kernlab , knitr , modeldata , randomForest , spelling , testthat , xml2 |
| depends | R (>= 2.10) |
| Contributors | RStudio |
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