embed v0.0.2

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by Max Kuhn View Source

Extra Recipes for Encoding Categorical Predictors

Factor predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. All encoding methods are supervised.

Functions in embed

Name	Description
reexports	Objects exported from other packages
step_embed	Encoding Factors into Multiple Columns
step_lencode_bayes	Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings
step_lencode_glm	Supervised Factor Conversions into Linear Functions using Likelihood Encodings
step_lencode_mixed	Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings
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Details

License	GPL-2
Encoding	UTF-8
LazyData	true
RoxygenNote	6.1.1
ByteCompile	true
URL	https://tidymodels.github.io/embed
BugReports	https://github.com/tidymodels/embed/issues
NeedsCompilation	no
Packaged	2018-11-19 18:30:36 UTC; max
Repository	CRAN
Date/Publication	2018-11-19 19:00:15 UTC

suggests	covr , knitr , rmarkdown , testthat
imports	dplyr , generics , keras , lme4 , purrr , rlang , rstanarm , stats , tensorflow , tibble , tidyr , utils
depends	R (>= 3.1) , recipes (>= 0.1.4)
Contributors	RStudio

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