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  3. Modeling with tidymodels in R
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Collecting predictions and creating custom metrics

Using the last_fit() modeling workflow also saves time in collecting model predictions. Instead of manually creating a tibble of model results, there are helper functions that extract this information automatically.

In this exercise, you will use your trained model, telecom_last_fit, to create a tibble of model results on the test dataset as well as calculate custom performance metrics.

Your trained model, telecom_last_fit, has been loaded into this session.

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  • Create a tibble, last_fit_results, that has the predictions from your telecom_last_fit model.
  • Print the results to the console.