Exercise

Delayed flights with Gradient-Boosted Trees

You've previously built a classifier for flights likely to be delayed using a Decision Tree. In this exercise you'll compare a Decision Tree model to a Gradient-Boosted Trees model.

The flights data have been randomly split into flights_train and flights_test.

Instructions

100 XP

Import the classes required to create Decision Tree and Gradient-Boosted Tree classifiers.
Create Decision Tree and Gradient-Boosted Tree classifiers. Train on the training data.
Create an evaluator and calculate AUC on testing data for both classifiers. Which model performs better?
Find the number of trees and the relative importance of features in the Gradient-Boosted Tree classifier.