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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:

# install.packages("pak")
pak::pak("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:

• Getting started with cell segmentation data
• Getting started with Ames housing data

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 Posit 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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.