Package: bestNormalize 1.9.1.9000

bestNormalize: Normalizing Transformation Functions

Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ). ORQ normalization combines a rank-mapping approach with a shifted logit approximation that allows the transformation to work on data outside the original domain. It is also able to handle new data within the original domain via linear interpolation. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the ordered quantile normalization transformation. It estimates the normalization efficacy of other commonly used transformations, and it allows users to specify custom transformations or normalization statistics. Finally, functionality can be integrated into a machine learning workflow via recipes.

Authors:Ryan Andrew Peterson [aut, cre]

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bestNormalize.pdf |bestNormalize.html
bestNormalize/json (API)
NEWS

# Install 'bestNormalize' in R:
install.packages('bestNormalize', repos = c('https://petersonr.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/petersonr/bestnormalize/issues

Datasets:
  • autotrader - Prices of 6,283 cars listed on Autotrader

On CRAN:

10.67 score 39 stars 5 packages 436 scripts 3.1k downloads 16 mentions 19 exports 81 dependencies

Last updated 9 months agofrom:46c0ea73e5. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 05 2024
R-4.5-winOKNov 05 2024
R-4.5-linuxOKNov 05 2024
R-4.4-winOKNov 05 2024
R-4.4-macOKNov 05 2024
R-4.3-winOKNov 05 2024
R-4.3-macOKNov 05 2024

Exports:arcsinh_xbestLogConstantbestNormalizebinarizeboxcoxcenter_scaledouble_reverse_logexp_xlambertlog_xno_transformorderNormrequired_pkgssqrt_xstep_best_normalizestep_bestNormalizestep_bestNormalize_newstep_orderNormyeojohnson

Dependencies:butcherclasscliclockcodetoolscolorspacecpp11crayondata.tablediagramdigestdoParalleldoRNGdplyrfansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelingLambertWlamWlatticelavalifecyclelistenvlobstrlubridatemagrittrMASSMatrixmgcvmunsellnlmennetnortestnumDerivparallellypillarpkgconfigplyrprettyunitsprodlimprogressrpurrrR6RColorBrewerRcppRcppParallelrecipesreshape2rlangrngtoolsrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr

Using the bestNormalize Package

Rendered frombestNormalize.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2023-03-08
Started: 2017-11-06

Customization within bestNormalize

Rendered fromcustomization.Rmdusingknitr::rmarkdownon Nov 05 2024.

Last update: 2022-06-13
Started: 2020-05-20

Readme and manuals

Help Manual

Help pageTopics
bestNormalize: Flexibly calculate the best normalizing transformation for a vectorbestNormalize-package
arcsinh(x) Transformationarcsinh_x predict.arcsinh_x print.arcsinh_x
Prices of 6,283 cars listed on Autotraderautotrader
Calculate and perform best normalizing log transformation (experimental)bestLogConstant predict.bestLogConstant print.bestLogConstant
Calculate and perform best normalizing transformationbestNormalize predict.bestNormalize print.bestNormalize tidy.bestNormalize
Binarizebinarize predict.binarize print.binarize
Box-Cox Normalizationboxcox predict.boxcox print.boxcox
Double Reverse Log(x + a) Transformationdouble_reverse_log predict.double_reverse_log print.double_reverse_log
exp(x) Transformationexp_x predict.exp_x print.exp_x
Lambert W x F Normalizationlambert predict.lambert print.lambert
Log(x + a) Transformationlog_x predict.log_x print.log_x
Identity transformation and center/scale transformcenter_scale no_transform predict.center_scale predict.no_transform print.center_scale print.no_transform tidy.no_transform
Calculate and perform Ordered Quantile normalizing transformationorderNorm predict.orderNorm print.orderNorm
Transformation plottingplot.bestNormalize plot.boxcox plot.lambert plot.orderNorm plot.yeojohnson
sqrt(x + a) Normalizationpredict.sqrt_x print.sqrt_x sqrt_x
Run bestNormalize transformation for 'recipes' implementationaxe_env.step_best_normalize step_bestNormalize step_bestNormalize_new step_best_normalize tidy.step_best_normalize
ORQ normalization (orderNorm) for 'recipes' implementationaxe_env.step_orderNorm step_orderNorm tidy.step_orderNorm
Yeo-Johnson Normalizationpredict.yeojohnson print.yeojohnson yeojohnson