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Exercise

Ordering of step_*() functions

The step_*() functions within a recipe are carried out in sequential order. It's important to keep this in mind so that you avoid unexpected results in your feature engineering pipeline!

In this exercise, you will combine different step_*() functions into a single recipe and see what effect the ordering of step_*() functions has on the final result.

The telecom_training and telecom_test datasets have been loaded into this session.

Instructions 1/4
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  • 1
    • Specify the telecom_recipe_1 object to normalize all numeric predictors and then create dummy variables for all nominal predictors in the training data, telecom_training.
    • Select columns by role in your recipe specification.
  • 2
    • Train telecom_recipe_1 and use it to transform the test data, telecom_test.
  • 3
    • Now specify telecom_recipe_2 to create dummy variables for all nominal predictors and then normalize all numeric predictors in the training data, telecom_training.
    • Select columns by role in your recipe specification.
  • 4
    • Train telecom_recipe_2 and use it to transform the test data, telecom_test.
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