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Safely Make a fitted workflow from a model spec tibble.

Usage

internal_make_fitted_wflw(.model_tbl, .splits_obj)

Arguments

.model_tbl

The model table that is generated from a function like fast_regression_parsnip_spec_tbl(), must have a class of "tidyaml_mod_spec_tbl". This is meant to be used after the function internal_make_wflw() has been run and the tibble has been saved.

.splits_obj

The splits object from the auto_ml function. It is internal to the auto_ml_ function.

Value

A list object of workflows.

Details

Create a fitted parnsip model from a workflow object.

Author

Steven P. Sanderson II, MPH

Examples

library(recipes, quietly = TRUE)

mod_spec_tbl <- fast_regression_parsnip_spec_tbl(
  .parsnip_eng = c("lm","glm"),
  .parsnip_fns = "linear_reg"
)

rec_obj <- recipe(mpg ~ ., data = mtcars)
splits_obj <- create_splits(mtcars, "initial_split")

mod_tbl <- mod_spec_tbl |>
  mutate(wflw = full_internal_make_wflw(mod_spec_tbl, rec_obj))

internal_make_fitted_wflw(mod_tbl, splits_obj)
#> [[1]]
#> ══ Workflow [trained] ══════════════════════════════════════════════════════════
#> Preprocessor: Recipe
#> Model: linear_reg()
#> 
#> ── Preprocessor ────────────────────────────────────────────────────────────────
#> 0 Recipe Steps
#> 
#> ── Model ───────────────────────────────────────────────────────────────────────
#> 
#> Call:
#> stats::lm(formula = ..y ~ ., data = data)
#> 
#> Coefficients:
#> (Intercept)          cyl         disp           hp         drat           wt  
#>    10.09884     -0.23530      0.01072     -0.02823      1.78879     -3.89387  
#>        qsec           vs           am         gear         carb  
#>     1.22259     -1.16046      3.96176     -1.47540      0.61497  
#> 
#> 
#> [[2]]
#> ══ Workflow [trained] ══════════════════════════════════════════════════════════
#> Preprocessor: Recipe
#> Model: linear_reg()
#> 
#> ── Preprocessor ────────────────────────────────────────────────────────────────
#> 0 Recipe Steps
#> 
#> ── Model ───────────────────────────────────────────────────────────────────────
#> 
#> Call:  stats::glm(formula = ..y ~ ., family = stats::gaussian, data = data)
#> 
#> Coefficients:
#> (Intercept)          cyl         disp           hp         drat           wt  
#>    10.09884     -0.23530      0.01072     -0.02823      1.78879     -3.89387  
#>        qsec           vs           am         gear         carb  
#>     1.22259     -1.16046      3.96176     -1.47540      0.61497  
#> 
#> Degrees of Freedom: 23 Total (i.e. Null);  13 Residual
#> Null Deviance:	    894.5 
#> Residual Deviance: 103.2 	AIC: 127.1
#>