R: Automatic Machine Learning with 'tidymodels'

# Automatic Machine Learning with 'tidymodels'

## Documentation for package ‘tidyAML’ version 0.0.6

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

check_duplicate_rows | Check for Duplicate Rows in a Data Frame
core_packages | Functions to Install all Core Libraries
create_model_spec | Generate Model Specification calls to 'parsnip'
create_splits | Utility Create Splits Object
create_workflow_set | Create a Workflow Set Object
extract_model_spec | Extract A Model Specification
extract_regression_residuals | Extract Residuals from Fast Regression Models
extract_tunable_params | Extract Tunable Parameters from Model Specifications
extract_wflw | Extract A Model Workflow
extract_wflw_fit | Extract A Model Fitted Workflow
extract_wflw_pred | Extract A Model Workflow Predictions
fast_classification | Generate Model Specification calls to 'parsnip'
fast_classification_parsnip_spec_tbl | Utility Classification call to 'parsnip'
fast_regression | Generate Model Specification calls to 'parsnip'
fast_regression_parsnip_spec_tbl | Utility Regression call to 'parsnip'
full_internal_make_wflw | Full Internal Workflow for Model and Recipe
get_model | Get a Model
install_deps | Functions to Install all Core Libraries
internal_make_fitted_wflw | Internals Safely Make a Fitted Workflow from Model Spec tibble
internal_make_spec_tbl | Internals Make a Model Spec tibble
internal_make_wflw | Internals Safely Make Workflow from Model Spec tibble
internal_make_wflw_gee_lin_reg | Internals Safely Make Workflow for GEE Linear Regression
internal_make_wflw_predictions | Internals Safely Make Predictions on a Fitted Workflow from Model Spec tibble
internal_set_args_to_tune | Internals Make a Tunable Model Specification
load_deps | Functions to Install all Core Libraries
make_classification_base_tbl | Internals Make Base Classification Tibble
make_regression_base_tbl | Internals Make Base Regression Tibble
match_args | Match function arguments
plot_regression_predictions | Create ggplot2 plot of regression predictions
plot_regression_residuals | Create ggplot2 plot of regression residuals
quantile_normalize | Perform quantile normalization on a numeric matrix/data.frame