add_woe()
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Add WoE in a data frame |
dictionary()
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Weight of evidence dictionary |
is_tf_available()
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Test to see if tensorflow is available |
step_discretize_cart() tidy(<step_discretize_cart>)
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Discretize numeric variables with CART |
step_discretize_xgb() tidy(<step_discretize_xgb>)
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Discretize numeric variables with XgBoost |
step_embed() tidy(<step_embed>) embed_control()
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Encoding Factors into Multiple Columns |
step_feature_hash() tidy(<step_feature_hash>)
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Dummy Variables Creation via Feature Hashing |
step_lencode_bayes() tidy(<step_lencode_bayes>)
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Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings |
step_lencode_glm() tidy(<step_lencode_glm>)
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Supervised Factor Conversions into Linear Functions using Likelihood Encodings |
step_lencode_mixed() tidy(<step_lencode_mixed>)
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Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodings |
step_umap() tidy(<step_umap>)
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Supervised and unsupervised uniform manifold approximation and projection (UMAP) |
step_woe() tidy(<step_woe>)
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Weight of evidence transformation |
woe_table()
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Crosstable with woe between a binary outcome and a predictor variable. |