Tune along the grid

After creating the tuning grid and a dummy specification, you need to fit a model on every grid point and evaluate the resulting model. This is very easy in the tidymodels framework using the tune_grid() function, as introduced in the slides.

In the remaining exercises, you will use the credit card customers dataset, which has the following columns:

still_customer: flag (yes or no) that indicates if a customer is still an active customer
total_trans_amt: total sum of transactions in USD
customer_age: age of the customer
income_category: labels like $60K - $80K or Less than $40K to indicate the category of yearly income
… and 16 more columns.

Feel free to inspect the customers tibble in the console! The results of the previous exercise, tree_grid and tune_spec, are still loaded.

Create three cross-validation folds of your dataset and save them as folds.
Create tune_results by tuning the specification along the grid using all predictors to predict still_customer, your CV folds as resamples, and metric_set(accuracy).
Use autoplot() to plot the tuning results.

Exercise

Tune along the grid

Instructions