R-hardhat
Port variant standard
Summary Construct Modeling Packages
Package version 1.3.1
Homepage https://github.com/tidymodels/hardhat
Keywords cran
Maintainer CRAN Automaton
License Not yet specified
Other variants There are no other variants.
Ravenports Buildsheet | History
Ravensource Port Directory | History
Last modified 03 FEB 2024, 15:41:37 UTC
Port created 22 FEB 2022, 02:10:24 UTC
Subpackage Descriptions
single hardhat: Construct Modeling Packages Building modeling packages is hard. A large amount of effort generally goes into providing an implementation for a new method that is efficient, fast, and correct, but often less emphasis is put on the user interface. A good interface requires specialized knowledge about S3 methods and formulas, which the average package developer might not have. The goal of 'hardhat' is to reduce the burden around building new modeling packages by providing functionality for preprocessing, predicting, and validating input.
Configuration Switches (platform-specific settings discarded)
This port has no build options.
Package Dependencies by Type
Build (only) gmake:primary:standard
R:primary:standard
icu:dev:standard
Build and Runtime R-cli:single:standard
R-glue:single:standard
R-rlang:single:standard
R-tibble:single:standard
R-vctrs:single:standard
Runtime (only) R:primary:standard
R:nls:standard
Download groups
main mirror://CRAN/src/contrib
https://loki.dragonflybsd.org/cranfiles/
Distribution File Information
0ea674778656a00206a1e76cf09aabff4cc18df670e27b9304ae1ce0fdde1b6c 610829 CRAN/hardhat_1.3.1.tar.gz
Ports that require R-hardhat:standard
R-dials:standard Tools for Creating Tuning Parameter Values
R-parsnip:standard Common API to Modeling and Analysis Functions
R-recipes:standard Preprocessing Tools to Create Design Matrices
R-tidymodels:standard Easily Install and Load the 'Tidymodels' Packages
R-tune:standard Tidy Tuning Tools
R-workflows:standard Modeling Workflows
R-workflowsets:standard Create a Collection of 'tidymodels' Workflows
R-yardstick:standard Tidy Characterizations of Model Performance