Exercise

Comparing model performance profiles

The benefit of the collect_metrics() function is that it returns a tibble of cross validation results. This makes it easy to calculate custom summary statistics with the dplyr package.

In this exercise, you will use dplyr to explore the cross validation results of your decision tree and logistic regression models.

Your cross validation results, loans_dt_rs and loans_logistic_rs have been loaded into your session.

Instructions 1/2

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  • 1
    • Collect the detailed cross validation results for your decision tree model.
    • Calculate the minimum, median, and maximum estimated metric values by metric type.
  • 2
    • Collect the detailed cross validation results for your logistic regression model.
    • Calculate the minimum, median, and maximum estimated metric values by metric type.