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?
For the Gradient-Boosted Tree classifier print the number of trees and the relative importance of features.