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Exercise

Feature importances

Although some candy attributes, such as chocolate, may be extremely popular, it doesn't mean they will be important to model prediction. After a random forest model has been fit, you can review the model's attribute, .feature_importances_, to see which variables had the biggest impact. You can check how important each variable was in the model by looping over the feature importance array using enumerate().

If you are unfamiliar with Python's enumerate() function, it can loop over a list while also creating an automatic counter.

Instructions
100 XP
  • Loop through the feature importance output of rfr.
  • Print the column names of X_train and the importance score for that column.