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embed (version 1.1.2)

Extra Recipes for Encoding Predictors

Description

Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models or nonlinear models can be used. There are also functions for dimension reduction and other approaches.

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Install

install.packages('embed')

Monthly Downloads

1,517

Version

1.1.2

License

MIT + file LICENSE

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Maintainer

Emil Hvitfeldt

Last Published

August 17th, 2023

Functions in embed (1.1.2)

reexports

Objects exported from other packages
required_pkgs.step_collapse_cart

S3 methods for tracking which additional packages are needed for steps.
step_pca_truncated

Truncated PCA Signal Extraction
step_umap

Supervised and unsupervised uniform manifold approximation and projection (UMAP)
step_feature_hash

Dummy Variables Creation via Feature Hashing
step_lencode_bayes

Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings
tunable.step_discretize_cart

tunable methods for embed
step_pca_sparse

Sparse PCA Signal Extraction
step_pca_sparse_bayes

Sparse Bayesian PCA Signal Extraction
step_lencode_glm

Supervised Factor Conversions into Linear Functions using Likelihood Encodings
step_woe

Weight of evidence transformation
step_discretize_xgb

Discretize numeric variables with XgBoost
tidy.step_collapse_cart

Tidy the Result of a Recipe
step_embed

Encoding Factors into Multiple Columns
woe_table

Crosstable with woe between a binary outcome and a predictor variable.
step_lencode_mixed

Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings
embed-package

embed: Extra Recipes for Encoding Predictors
is_tf_available

Test to see if tensorflow is available
dictionary

Weight of evidence dictionary
step_discretize_cart

Discretize numeric variables with CART
solubility

Compound solubility data
add_woe

Add WoE in a data frame
step_collapse_stringdist

collapse factor levels using stringdist
step_collapse_cart

Supervised Collapsing of Factor Levels