as_workflow_set: Convert existing objects to a workflow set

In workflowsets: Create a Collection of 'tidymodels' Workflows

Convert existing objects to a workflow set

Description

Use existing objects to create a workflow set. A list of objects that are either simple workflows or objects that have class "tune_results" can be converted into a workflow set.

Usage

as_workflow_set(...)

Arguments

...

One or more named objects. Names should be unique and the objects should have at least one of the following classes: workflow, iteration_results, tune_results, resample_results, or tune_race. Each tune_results element should also contain the original workflow (accomplished using the save_workflow option in the control function).

Value

A workflow set. Note that the option column will not reflect the options that were used to create each object.

Note

The package supplies two pre-generated workflow sets, two_class_set and chi_features_set, and associated sets of model fits two_class_res and chi_features_res.

The ⁠two_class_*⁠ objects are based on a binary classification problem using the two_class_dat data from the modeldata package. The six models utilize either a bare formula or a basic recipe utilizing recipes::step_YeoJohnson() as a preprocessor, and a decision tree, logistic regression, or MARS model specification. See ?two_class_set for source code.

The ⁠chi_features_*⁠ objects are based on a regression problem using the Chicago data from the modeldata package. Each of the three models utilize a linear regression model specification, with three different recipes of varying complexity. The objects are meant to approximate the sequence of models built in Section 1.3 of Kuhn and Johnson (2019). See ?chi_features_set for source code.

Examples

# ------------------------------------------------------------------------------
# Existing results

# Use the already worked example to show how to add tuned
# objects to a workflow set
two_class_res

results <- two_class_res %>% purrr::pluck("result")
names(results) <- two_class_res$wflow_id

# These are all objects that have been resampled or tuned:
purrr::map_chr(results, ~ class(.x)[1])

# Use rlang's !!! operator to splice in the elements of the list
new_set <- as_workflow_set(!!!results)

# ------------------------------------------------------------------------------
# Make a set from unfit workflows

library(parsnip)
library(workflows)

lr_spec <- logistic_reg()

main_effects <-
  workflow() %>%
  add_model(lr_spec) %>%
  add_formula(Class ~ .)

interactions <-
  workflow() %>%
  add_model(lr_spec) %>%
  add_formula(Class ~ (.)^2)

as_workflow_set(main = main_effects, int = interactions)

workflowsets documentation built on April 7, 2023, 1:05 a.m.