tidyfit: Regularized Linear Modeling with Tidy Data

An extension to the 'R' tidy data environment for automated machine learning. The package allows fitting and cross validation of linear regression and classification algorithms on grouped data.

Version: 0.6.0
Depends: R (≥ 3.5)
Imports: broom, crayon, dials, dplyr, furrr, magrittr, MASS, methods, progressr, purrr, rlang, rsample, stats, tibble, tidyr, utils, yardstick
Suggests: arm, bestglm, BMS, CORElearn, e1071, gets, glmnet, hfr, kableExtra, knitr, lme4, lmtest, lubridate, mboost, mRMRe, MSwM, pls, quantreg, randomForest, sandwich, shrinkTVP, tidyverse, rmarkdown
Published: 2022-11-25
Author: Johann Pfitzinger [aut, cre]
Maintainer: Johann Pfitzinger <johann.pfitzinger at gmail.com>
License: GPL-3
URL: https://tidyfit.unchartedml.com, https://github.com/jpfitzinger/tidyfit
NeedsCompilation: no
Materials: README NEWS
CRAN checks: tidyfit results


Reference manual: tidyfit.pdf
Vignettes: Accessing Fitted Model Objects
Predicting Boston House Prices
Bootstrapping Confidence Intervals
Feature Selection
Multinomial Classification
Rolling Window Time Series Regression
Time-varying parameters vs. rolling windows


Package source: tidyfit_0.6.0.tar.gz
Windows binaries: r-devel: tidyfit_0.5.1.zip, r-release: tidyfit_0.5.1.zip, r-oldrel: tidyfit_0.5.1.zip
macOS binaries: r-release (arm64): tidyfit_0.5.1.tgz, r-oldrel (arm64): tidyfit_0.5.1.tgz, r-release (x86_64): tidyfit_0.6.0.tgz, r-oldrel (x86_64): tidyfit_0.6.0.tgz
Old sources: tidyfit archive


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