Package: embed 1.1.4.9000

Emil Hvitfeldt

embed: Extra Recipes for Encoding Predictors

Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models <arxiv:1611.09477> or nonlinear models <arxiv:1604.06737> can be used. There are also functions for dimension reduction and other approaches.

Authors:Emil Hvitfeldt [aut, cre], Max Kuhn [aut], Posit Software, PBC [cph, fnd]

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NEWS

# Install 'embed' in R:
install.packages('embed', repos = c('https://tidymodels.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tidymodels/embed/issues

Pkgdown site:https://embed.tidymodels.org

Datasets:

On CRAN:

9.30 score 142 stars 1.1k scripts 1.5k downloads 1 mentions 20 exports 69 dependencies

Last updated 1 months agofrom:2fd60a08cf. Checks:OK: 1 NOTE: 6. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 22 2024
R-4.5-winNOTEDec 22 2024
R-4.5-linuxNOTEDec 22 2024
R-4.4-winNOTEDec 22 2024
R-4.4-macNOTEDec 22 2024
R-4.3-winNOTEDec 22 2024
R-4.3-macNOTEDec 22 2024

Exports:add_woedictionaryembed_controlrequired_pkgsstep_collapse_cartstep_collapse_stringdiststep_discretize_cartstep_discretize_xgbstep_embedstep_feature_hashstep_lencode_bayesstep_lencode_glmstep_lencode_mixedstep_pca_sparsestep_pca_sparse_bayesstep_pca_truncatedstep_umapstep_woetidytunable

Dependencies:BHclasscliclockcodetoolscpp11data.tablediagramdigestdplyrdqrngfansiFNNfurrrfuturefuture.applygenericsglobalsgluegowerhardhatipredirlbaKernSmoothlatticelavalifecyclelistenvlubridatemagrittrMASSMatrixnnetnumDerivparallellypillarpkgconfigprodlimprogressrpurrrR6RcppRcppAnnoyRcppEigenRcppProgressrecipesrlangrpartrsampleRSpectrashapesitmoslidersparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8uwotvctrswarpwithr

Readme and manuals

Help Manual

Help pageTopics
Add WoE in a data frameadd_woe
Weight of evidence dictionarydictionary
Compound solubility datasolubility
Supervised Collapsing of Factor Levelsstep_collapse_cart tidy.step_collapse_cart
collapse factor levels using stringdiststep_collapse_stringdist tidy.step_collapse_stringdist
Discretize numeric variables with CARTstep_discretize_cart tidy.step_discretize_cart
Discretize numeric variables with XgBooststep_discretize_xgb tidy.step_discretize_xgb
Encoding Factors into Multiple Columnsembed_control step_embed tidy.step_embed
Dummy Variables Creation via Feature Hashingstep_feature_hash tidy.step_feature_hash
Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodingsstep_lencode_bayes tidy.step_lencode_bayes
Supervised Factor Conversions into Linear Functions using Likelihood Encodingsstep_lencode_glm tidy.step_lencode_glm
Supervised Factor Conversions into Linear Functions using Bayesian Likelihood Encodingsstep_lencode_mixed tidy.step_lencode_mixed
Sparse PCA Signal Extractionstep_pca_sparse tidy.step_pca_sparse
Sparse Bayesian PCA Signal Extractionstep_pca_sparse_bayes tidy.step_pca_sparse_bayes
Truncated PCA Signal Extractionstep_pca_truncated tidy.step_pca_truncated
Supervised and unsupervised uniform manifold approximation and projection (UMAP)step_umap tidy.step_umap
Weight of evidence transformationstep_woe tidy.step_woe
Crosstable with woe between a binary outcome and a predictor variable.woe_table