Preprocessing and Feature Engineering Steps for Modeling R package recipes version 1.3.3 A recipe prepares your data for modeling. We provide an extensible framework for pipeable sequences of feature engineering steps provides preprocessing tools to be applied to data. Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting processed output can then be used as inputs for statistical or machine learning models. Software Depends: dplyr (>= 1.1.0), R (>= 4.1) Imports: cli, clock (>= 0.6.1), generics (>= 0.1.2), glue, gower, hardhat (>= 1.4.1), ipred (>= 0.9-12), lifecycle (>= 1.0.3), lubridate (>= 1.8.0), magrittr, Matrix, purrr (>= 1.0.0), rlang (>= 1.1.0), sparsevctrs (>= 0.3.3), stats, tibble, tidyr (>= 1.0.0), tidyselect (>= 1.2.0), timeDate, utils, vctrs (>= 0.5.0), withr Suggests: covr, ddalpha, dials (>= 1.2.0), dimRed, fastICA, ggplot2, igraph (>= 2.1.1), kernlab, knitr, methods, mixOmics, modeldata (>= 0.1.1), parsnip (>= 1.2.0), RANN, RcppRoll, rmarkdown, rpart, rsample, RSpectra, splines2, testthat (>= 3.3.0), workflows, xml2 Max Kuhn <max@posit.co> Comprehensive R Archive Network (CRAN) Max Kuhn [aut, cre], Hadley Wickham [aut], Emil Hvitfeldt [aut], Posit Software, PBC [cph, fnd] (ROR: <https://ror.org/03wc8by49>) MIT + file LICENSE (https://CRAN.R-project.org/package=recipes/LICENSE) 2026-05-30 application/tgz https://CRAN.R-project.org/package=recipes doi:10.32614/CRAN.package.recipes