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tune

The goal of tune is to facilitate the tuning of hyper-parameters 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 a few package vignettes, the first being the Getting Started document. Other examples resources:

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Version

Install

install.packages('tune')

Monthly Downloads

30,607

Version

0.1.0

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Maintainer

Max Kuhn

Last Published

April 2nd, 2020

Functions in tune (0.1.0)

example_ames_knn

Example Analysis of Ames Housing Data
load_pkgs

Quietly load package namespace
expo_decay

Exponential decay function
merge.recipe

Merge parameter grid values into objects
tune_grid

Model tuning via grid search
extract_recipe

Convenience functions to extract model or recipe
tune_args

Determine arguments tagged for tuning
finalize_model

Splice final parameters into objects
control_bayes

Control aspects of the Bayesian search process
prob_improve

Acquisition function for scoring parameter combinations
parameters.workflow

Determination of parameter sets for other objects
tune_bayes

Bayesian optimization of model parameters.
control_grid

Control aspects of the grid search process
last_fit

Fit the final best model to the training set and evaluate the test set
fit_resamples

Fit multiple models via resampling
min_grid

Determine the minimum set of model fits
show_best

Investigate best tuning parameters
collect_predictions

Obtain and format results produced by tuning functions
reexports

Objects exported from other packages
tune

A placeholder function for argument values that are to be tuned.
autoplot.tune_results

Plot tuning search results
outcome_names

Determine names of the outcome data in a workflow
tunable

Find recommended methods for generating parameter values