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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:

Contributing

This project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

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Version

Install

install.packages('tune')

Monthly Downloads

26,618

Version

0.1.2

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Maintainer

Max Kuhn

Last Published

November 17th, 2020

Functions in tune (0.1.2)

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