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Exercise

Exploring the loans dataset

The workflows package provides the ability to bundle parsnip models and recipe objects into a single modeling workflow object. This makes managing a machine learning project much easier and removes the need to keep track of multiple modeling objects.

In this exercise, you will be working with the loans_df dataset, which contains financial information on consumer loans at a bank. The outcome variable in this data is loan_default.

You will create a decision tree model object and specify a feature engineering pipeline for the loan data. The loans_df tibble has been loaded into your session.

Instructions 1/2

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  • Create a data split object, loans_split, using the loans_df tibble making sure to stratify by the outcome variable.
  • Create the training dataset.
  • Create the test dataset.