Full equation from a stacked model

[lisalendway]

I'm wondering how to get the full equation from a stacked model, including the intercept? I see one in the last part of section 20.2 (right above the start of 20.3) in tidymodeling with R, but I can't seem to figure out where that might be buried in the results. Any help is appreciated. Thanks!

In case you're curious why I want these, I'm trying to make sure I fully understand where the scores come from when there is a binary response since the "stacked" scores are MUCH lower than the scores from the individual models.

[Max]

Sure, you can get this pretty easily. Once the stack is blended, there is an equation sub-object that has the generalized linear model prediction equation.

Here's a regression example from the docs:

library(tidymodels)
library(stacks)
library(rlang)
#> 
#> Attaching package: 'rlang'
#> The following objects are masked from 'package:purrr':
#> 
#>     %@%, flatten, flatten_chr, flatten_dbl, flatten_int, flatten_lgl,
#>     flatten_raw, invoke, splice

tidymodels_prefer()

# from ?blend_predictions

reg_st <- 
  stacks() %>%
  add_candidates(reg_res_lr) %>%
  add_candidates(reg_res_svm) %>%
  add_candidates(reg_res_sp)

# evaluate the data stack
reg_st <- 
  reg_st %>%
  blend_predictions()

reg_st$equations
#> $numeric
#> $.pred
#> -8.84601130389494 + (reg_res_svm_1_3 * 0.63844261429) + (reg_res_sp_10_1 * 
#>     0.0481870055572203) + (reg_res_sp_03_1 * 0.485948459397137)
#> 
#> attr(,"class")
#> [1] "elnet_numeric"

# An R expression: 
reg_st$equations$numeric$.pred
#> -8.84601130389494 + (reg_res_svm_1_3 * 0.63844261429) + (reg_res_sp_10_1 * 
#>     0.0481870055572203) + (reg_res_sp_03_1 * 0.485948459397137)

# Make into text: 
expr_deparse(reg_st$equations$numeric$.pred, width = 200)
#> [1] "-8.84601130389494 + (reg_res_svm_1_3 * 0.63844261429) + (reg_res_sp_10_1 * 0.0481870055572203) + (reg_res_sp_03_1 * 0.485948459397137)"

^{Created on 2023-09-16 with reprex v2.0.2}

[lisalendway]

Thanks for the quick response. I looked in the equations output and somehow missed that