Package: tidyAML 0.0.5.9000

tidyAML: Automatic Machine Learning with 'tidymodels'

The goal of this package will be to provide a simple interface for automatic machine learning that fits the 'tidymodels' framework. The intention is to work for regression and classification problems with a simple verb framework.

Authors:Steven Sanderson [aut, cre, cph]

tidyAML_0.0.5.9000.tar.gz
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tidyAML.pdf |tidyAML.html
tidyAML/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/spsanderson/tidyaml/issues

On CRAN:

automatic-machine-learningautomlclassificationmachine-learningparsnipr-languager-programmingregressiontidytidymodelstidyverse

37 exports 64 stars 7.61 score 88 dependencies 1 dependents 35 scripts 248 downloads

Last updated 6 months agofrom:c09c15ac69. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 24 2024
R-4.5-winOKSep 24 2024
R-4.5-linuxOKSep 24 2024
R-4.4-winOKSep 24 2024
R-4.4-macOKSep 24 2024
R-4.3-winOKSep 24 2024
R-4.3-macOKSep 24 2024

Exports::=.data%>%as_labelas_namecheck_duplicate_rowscore_packagescreate_model_speccreate_splitscreate_workflow_setenquoenquosextract_model_specextract_regression_residualsextract_wflwextract_wflw_fitextract_wflw_predfast_classificationfast_classification_parsnip_spec_tblfast_regressionfast_regression_parsnip_spec_tblfull_internal_make_wflwget_modelinstall_depsinternal_make_fitted_wflwinternal_make_spec_tblinternal_make_wflwinternal_make_wflw_gee_lin_reginternal_make_wflw_predictionsinternal_set_args_to_tuneload_depsmake_classification_base_tblmake_regression_base_tblmatch_argsplot_regression_predictionsplot_regression_residualsquantile_normalize

Dependencies:backportsbroomclasscliclockcodetoolscolorspacecpp11data.tablediagramdialsDiceDesigndigestdoFuturedplyrfansifarverforcatsforeachfurrrfuturefuture.applygenericsggplot2globalsgluegowerGPfitgtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalhslifecyclelistenvlubridatemagrittrMASSMatrixmgcvmodelenvmunsellnlmennetnumDerivparallellyparsnippillarpkgconfigprettyunitsprodlimprogressrpurrrR6RColorBrewerRcpprecipesrlangrpartrsamplescalessfdshapesliderSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetunetzdbutf8vctrsviridisLitewarpwithrworkflowsworkflowsetsyardstick

Getting Started with tidyAML

Rendered fromgetting-started.Rmdusingknitr::rmarkdownon Sep 24 2024.

Last update: 2023-12-18
Started: 2022-12-01

Readme and manuals

Help Manual

Help pageTopics
Check for Duplicate Rows in a Data Framecheck_duplicate_rows
Functions to Install all Core Librariescore_packages
Generate Model Specification calls to 'parsnip'create_model_spec
Utility Create Splits Objectcreate_splits
Create a Workflow Set Objectcreate_workflow_set
Extract A Model Specificationextract_model_spec
Extract Residuals from Fast Regression Modelsextract_regression_residuals
Extract A Model Workflowextract_wflw
Extract A Model Fitted Workflowextract_wflw_fit
Extract A Model Workflow Predictionsextract_wflw_pred
Generate Model Specification calls to 'parsnip'fast_classification
Utility Classification call to 'parsnip'fast_classification_parsnip_spec_tbl
Generate Model Specification calls to 'parsnip'fast_regression
Utility Regression call to 'parsnip'fast_regression_parsnip_spec_tbl
Full Internal Workflow for Model and Recipefull_internal_make_wflw
Get a Modelget_model
Functions to Install all Core Librariesinstall_deps
Internals Safely Make a Fitted Workflow from Model Spec tibbleinternal_make_fitted_wflw
Internals Make a Model Spec tibbleinternal_make_spec_tbl
Internals Safely Make Workflow from Model Spec tibbleinternal_make_wflw
Internals Safely Make Workflow for GEE Linear Regressioninternal_make_wflw_gee_lin_reg
Internals Safely Make Predictions on a Fitted Workflow from Model Spec tibbleinternal_make_wflw_predictions
Internals Make a Tunable Model Specificationinternal_set_args_to_tune
Functions to Install all Core Librariesload_deps
Internals Make Base Classification Tibblemake_classification_base_tbl
Internals Make Base Regression Tibblemake_regression_base_tbl
Match function argumentsmatch_args
Create ggplot2 plot of regression predictionsplot_regression_predictions
Create ggplot2 plot of regression residualsplot_regression_residuals
Perform quantile normalization on a numeric matrix/data.framequantile_normalize