Extra Recipes for Encoding Categorical Predictors

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Documentation for package ‘embed’ version 0.0.6

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add_woe Add WoE in a data frame
dictionary Weight of evidence dictionary
embed_control Encoding Factors into Multiple Columns
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
step_umap Supervised and unsupervised uniform manifold approximation and projection (UMAP)
step_woe Weight of evidence transformation
tidy.step_embed Encoding Factors into Multiple Columns
tidy.step_lencode_bayes Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings
tidy.step_lencode_glm Supervised Factor Conversions into Linear Functions using Likelihood Encodings
tidy.step_lencode_mixed Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings
tidy.step_umap Supervised and unsupervised uniform manifold approximation and projection (UMAP)
tidy.step_woe Weight of evidence transformation
woe_table Crosstable with woe between a binary outcome and a predictor variable.