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  3. Extreme Gradient Boosting with XGBoost

Exercise

Cross-validating your XGBoost model

In this exercise, you'll go one step further by using the pipeline you've created to preprocess and cross-validate your model.

Instructions

100 XP
  • Create a pipeline called xgb_pipeline using steps.
  • Perform 10-fold cross-validation using cross_val_score(). You'll have to pass in the pipeline, X (as a dictionary, using .to_dict("records")), y, the number of folds you want to use, and scoring ("neg_mean_squared_error").
  • Print the 10-fold RMSE.