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Compare to a single classifier

You learned that boosted trees are among the best machine learning algorithms available. To underpin that, you will now compare the AUC of a boosted model to a simple decision tree classifier.

In this exercise, you will use the whole machine-learning pipeline from specification to evaluation.

The training data customers_train is still pre-loaded.

Diese Übung ist Teil des Kurses

Machine Learning with Tree-Based Models in R

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Interaktive Übung

Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.

set.seed(100)

# Specify, fit, predict, and combine with training data
predictions <- boost_tree() %>%
  set_mode("___") %>%
  set_engine("___") %>% 
  fit(still_customer ~ ., data = ___) %>%
  predict(new_data = ___, type = "___") %>% 
  bind_cols(___)

# Calculate AUC
roc_auc(___, 
        truth = ___, 
        estimate = ___)
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