Full Internal Workflow for Model and Recipe

This function creates a full internal workflow for a model and recipe combination.

Usage

full_internal_make_wflw(.model_tbl, .rec_obj)

Arguments

.model_tbl

A model specification table (tidyaml_mod_spec_tbl).

.rec_obj

A recipe object.

Value

The function returns a workflow object for the first model-recipe pair based on the internal function selected.

Details

The function checks if the input model specification table inherits the class 'tidyaml_mod_spec_tbl'. It then manipulates the input table, making adjustments for factors and creating a list of grouped models. For each model-recipe pair, it uses the appropriate internal function based on the model type to create a workflow object. The specific internal function is selected using a switch statement based on the class of the model.

See also

Other Utility: core_packages(), create_splits(), create_workflow_set(), fast_classification_parsnip_spec_tbl(), fast_regression_parsnip_spec_tbl(), install_deps(), load_deps(), match_args()

Author

Steven P. Sanderson II, MPH

Examples

library(dplyr)
library(recipes)

rec_obj <- recipe(mpg ~ ., data = mtcars)

mod_tbl <- make_regression_base_tbl()
mod_tbl <- mod_tbl |>
  filter(
    .parsnip_engine %in% c("lm", "glm") &
    .parsnip_fns == "linear_reg"
    )
class(mod_tbl) <- c("tidyaml_mod_spec_tbl", class(mod_tbl))
mod_spec_tbl <- internal_make_spec_tbl(mod_tbl)
result <- full_internal_make_wflw(mod_spec_tbl, rec_obj)
result
#> [[1]]
#> ══ Workflow ════════════════════════════════════════════════════════════════════
#> Preprocessor: Recipe
#> Model: linear_reg()
#> 
#> ── Preprocessor ────────────────────────────────────────────────────────────────
#> 0 Recipe Steps
#> 
#> ── Model ───────────────────────────────────────────────────────────────────────
#> Linear Regression Model Specification (regression)
#> 
#> Computational engine: lm 
#> 
#> 
#> [[2]]
#> ══ Workflow ════════════════════════════════════════════════════════════════════
#> Preprocessor: Recipe
#> Model: linear_reg()
#> 
#> ── Preprocessor ────────────────────────────────────────────────────────────────
#> 0 Recipe Steps
#> 
#> ── Model ───────────────────────────────────────────────────────────────────────
#> Linear Regression Model Specification (regression)
#> 
#> Computational engine: glm 
#> 
#>