Streamlining the modeling process

The last_fit() function is designed to streamline the modeling workflow in tidymodels. Instead of training your model on the training data and building a results tibble using the test data, last_fit() accomplishes this with one function.

In this exercise, you will train the same logistic regression model as you fit in the previous exercises, except with the last_fit() function.

Your data split object, telecom_split, and model specification, logistic_model, have been loaded into your session.

This exercise is part of the course

Modeling with tidymodels in R

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Exercise instructions

Pass your logistic_model object into the last_fit() function.
Predict canceled_service using avg_call_mins, avg_intl_mins, and monthly_charges.
Display the performance metrics of your trained model, telecom_last_fit.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Train model with last_fit()
telecom_last_fit <- ___ %>% 
  last_fit(___,
           split = ___)

# View test set metrics
telecom_last_fit %>% 
  ___

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