embed v0.1.2

0

Monthly downloads

0th

Percentile

Extra Recipes for Encoding Categorical Predictors

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

Functions in embed

Name Description
required_pkgs.step_lencode_bayes S3 methods for tracking which additional packages are needed for steps.
dictionary Weight of evidence dictionary
add_woe Add WoE in a data frame
is_tf_available Test to see if tensorflow is available
reexports Objects exported from other packages
step_embed Encoding Factors into Multiple Columns
step_discretize_cart Discretize numeric variables with CART
step_discretize_xgb Discretize numeric variables with XgBoost
step_feature_hash Dummy Variables Creation via Feature Hashing
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_umap Supervised and unsupervised uniform manifold approximation and projection (UMAP)
step_woe Weight of evidence transformation
woe_table Crosstable with woe between a binary outcome and a predictor variable.
tunable.step_embed tunable methods for embed
step_lencode_mixed Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings
No Results!

Last month downloads

Details

License GPL-2
Encoding UTF-8
LazyData true
RoxygenNote 7.1.1
ByteCompile true
URL https://embed.tidymodels.org, https://github.com/tidymodels/embed
BugReports https://github.com/tidymodels/embed/issues
NeedsCompilation no
Packaged 2020-10-17 16:50:00 UTC; max
Repository CRAN
Date/Publication 2020-10-17 17:20:02 UTC

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/embed)](http://www.rdocumentation.org/packages/embed)