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  • Created almost 6 years ago
  • Updated 3 months ago

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Repository Details

Easily install and load the tidymodels packages

tidymodels

R-CMD-check Codecov test coverage CRAN_Status_Badge Downloads lifecycle

Overview

tidymodels is a โ€œmeta-packageโ€ for modeling and statistical analysis that shares the underlying design philosophy, grammar, and data structures of the tidyverse.

It includes a core set of packages that are loaded on startup:

  • broom takes the messy output of built-in functions in R, such as lm, nls, or t.test, and turns them into tidy data frames.

  • dials has tools to create and manage values of tuning parameters.

  • dplyr contains a grammar for data manipulation.

  • ggplot2 implements a grammar of graphics.

  • infer is a modern approach to statistical inference.

  • parsnip is a tidy, unified interface to creating models.

  • purrr is a functional programming toolkit.

  • recipes is a general data preprocessor with a modern interface. It can create model matrices that incorporate feature engineering, imputation, and other help tools.

  • rsample has infrastructure for resampling data so that models can be assessed and empirically validated.

  • tibble has a modern re-imagining of the data frame.

  • tune contains the functions to optimize model hyper-parameters.

  • workflows has methods to combine pre-processing steps and models into a single object.

  • yardstick contains tools for evaluating models (e.g.ย accuracy, RMSE, etc.).

A list of all tidymodels functions across different CRAN packages can be found at https://www.tidymodels.org/find/.

You can install the released version of tidymodels from CRAN with:

install.packages("tidymodels")

Install the development version from GitHub with:

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

When loading the package, the versions and conflicts are listed:

library(tidymodels)
#> โ”€โ”€ Attaching packages โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ tidymodels 1.2.0 โ”€โ”€
#> โœ” broom        1.0.5      โœ” recipes      1.0.10
#> โœ” dials        1.2.1      โœ” rsample      1.2.0 
#> โœ” dplyr        1.1.4      โœ” tibble       3.2.1 
#> โœ” ggplot2      3.5.0      โœ” tidyr        1.3.1 
#> โœ” infer        1.0.6      โœ” tune         1.2.0 
#> โœ” modeldata    1.3.0      โœ” workflows    1.1.4 
#> โœ” parsnip      1.2.1      โœ” workflowsets 1.1.0 
#> โœ” purrr        1.0.2      โœ” yardstick    1.3.1
#> โ”€โ”€ Conflicts โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€ tidymodels_conflicts() โ”€โ”€
#> โœ– purrr::discard() masks scales::discard()
#> โœ– dplyr::filter()  masks stats::filter()
#> โœ– dplyr::lag()     masks stats::lag()
#> โœ– recipes::step()  masks stats::step()
#> โ€ข Learn how to get started at https://www.tidymodels.org/start/

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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