TMwR | Code and content for Tidy Modeling with R

I want to use purrr::map_* functions to extract info from multiple models involving linear regression method. I am first creating some random dataset. The dataset has three dependent variables, and one independent variable.

I tried to follow the examples in the

Link 1 - Sparse Matrix https://www.tidyverse.org/blog/2020/11/tidymodels-sparse-support/

Link 2 - Workflow_sets https://www.tmwr.org/workflow-sets.html

I had trouble including the blue print into the workflow sets.

In the examples where workflow_set is defined in link 2

I try to use tidymodels to tune the workflow with recipe and model parameters. When tuning a single workflow there is no problem. But when tuning a workflowsets with several workflows it always fails. Here is my codes:

Overview

I have produced four models using the tidymodels package with the data frame FID (see R-code below):

1. General Linear Model (glm)
2. Bagged Tree
3. Random Forest
4. Boosted Trees

The data frame contains three predictors:

1. Year (numeric)
2. Month (Factor)
3. Days (numeric)

The dependent variable is Frequency (numeric)

Aim

My aim is to unnest the best-fitted models (i.e. glm, bagged tree, random forest, boosted trees) to display the metrics RMSE and RSQ after conducting a 10 fold cross-validation from a tibble object produced using the function fit_samples().

Example of the tibble

I'm using a medical insurance data set to hone my modeling skills that looks like this: