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Exercise

Movie revenue prediction with CatBoost

Let's finish up this chapter on boosting by returning to the movies dataset! In this exercise, you'll build a CatBoostRegressor to predict the log-revenue. Remember that our best model so far is the AdaBoost model with a RMSE of 5.15.

Will CatBoost beat AdaBoost? We'll try to use a similar set of parameters to have a fair comparison.

Recall that these are the features we have used so far: 'budget', 'popularity', 'runtime', 'vote_average', and 'vote_count'. catboost has been imported for you as cb.

OBS: be careful not to use a classifier, or your session might expire!

Instructions

100 XP
  • Build and fit a CatBoostRegressor using 100 estimators, a learning rate of 0.1, and a max depth of 3.
  • Calculate the predictions for the test set and print the RMSE.