βœ… Quiz M6.04ΒΆ

Question

Gradient boosting are usually composed of (in comparison to random forest):

  • a) shallow trees

  • b) deep trees

  • c) using a subset of features

  • d) using all features

Question

Which of the hyperparameter(s) do not exist in random forest but exists in gradient boosting:

  • a) number of estimators

  • b) maximum depth

  • c) learning rate

Question

Which of the following options are correct about the benefits of ensemble models?

  • a) Better generalization performance

  • b) Reduced sensitivity to hyper-parameter tuning of individual predictors

  • c) Better interpretability