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:
bestNormalize_1.9.1.9000.tar.gz
bestNormalize_1.9.1.9000.zip(r-4.5)bestNormalize_1.9.1.9000.zip(r-4.4)bestNormalize_1.9.1.9000.zip(r-4.3)
bestNormalize_1.9.1.9000.tgz(r-4.4-any)bestNormalize_1.9.1.9000.tgz(r-4.3-any)
bestNormalize_1.9.1.9000.tar.gz(r-4.5-noble)bestNormalize_1.9.1.9000.tar.gz(r-4.4-noble)
bestNormalize_1.9.1.9000.tgz(r-4.4-emscripten)bestNormalize_1.9.1.9000.tgz(r-4.3-emscripten)
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')) |
Bug tracker:https://github.com/petersonr/bestnormalize/issues
- autotrader - Prices of 6,283 cars listed on Autotrader
Last updated 9 months agofrom:46c0ea73e5. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 05 2024 |
R-4.5-win | OK | Nov 05 2024 |
R-4.5-linux | OK | Nov 05 2024 |
R-4.4-win | OK | Nov 05 2024 |
R-4.4-mac | OK | Nov 05 2024 |
R-4.3-win | OK | Nov 05 2024 |
R-4.3-mac | OK | Nov 05 2024 |
Exports:arcsinh_xbestLogConstantbestNormalizebinarizeboxcoxcenter_scaledouble_reverse_logexp_xlambertlog_xno_transformorderNormrequired_pkgssqrt_xstep_best_normalizestep_bestNormalizestep_bestNormalize_newstep_orderNormyeojohnson
Dependencies:butcherclasscliclockcodetoolscolorspacecpp11crayondata.tablediagramdigestdoParalleldoRNGdplyrfansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelingLambertWlamWlatticelavalifecyclelistenvlobstrlubridatemagrittrMASSMatrixmgcvmunsellnlmennetnortestnumDerivparallellypillarpkgconfigplyrprettyunitsprodlimprogressrpurrrR6RColorBrewerRcppRcppParallelrecipesreshape2rlangrngtoolsrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
bestNormalize: Flexibly calculate the best normalizing transformation for a vector | bestNormalize-package |
arcsinh(x) Transformation | arcsinh_x predict.arcsinh_x print.arcsinh_x |
Prices of 6,283 cars listed on Autotrader | autotrader |
Calculate and perform best normalizing log transformation (experimental) | bestLogConstant predict.bestLogConstant print.bestLogConstant |
Calculate and perform best normalizing transformation | bestNormalize predict.bestNormalize print.bestNormalize tidy.bestNormalize |
Binarize | binarize predict.binarize print.binarize |
Box-Cox Normalization | boxcox predict.boxcox print.boxcox |
Double Reverse Log(x + a) Transformation | double_reverse_log predict.double_reverse_log print.double_reverse_log |
exp(x) Transformation | exp_x predict.exp_x print.exp_x |
Lambert W x F Normalization | lambert predict.lambert print.lambert |
Log(x + a) Transformation | log_x predict.log_x print.log_x |
Identity transformation and center/scale transform | center_scale no_transform predict.center_scale predict.no_transform print.center_scale print.no_transform tidy.no_transform |
Calculate and perform Ordered Quantile normalizing transformation | orderNorm predict.orderNorm print.orderNorm |
Transformation plotting | plot.bestNormalize plot.boxcox plot.lambert plot.orderNorm plot.yeojohnson |
sqrt(x + a) Normalization | predict.sqrt_x print.sqrt_x sqrt_x |
Run bestNormalize transformation for 'recipes' implementation | axe_env.step_best_normalize step_bestNormalize step_bestNormalize_new step_best_normalize tidy.step_best_normalize |
ORQ normalization (orderNorm) for 'recipes' implementation | axe_env.step_orderNorm step_orderNorm tidy.step_orderNorm |
Yeo-Johnson Normalization | predict.yeojohnson print.yeojohnson yeojohnson |