✅ Quiz M6.03

Question

When compared to random forests, gradient boosting is usually trained using:

• a) shallower trees

• b) deeper trees

• c) a subset of features

• d) all features

Select all answers that apply

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

Select all answers that apply

Question

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

• a) Better generalization performance

• b) Reduced sensitivity to hyperparameter tuning of individual predictors

• c) Better interpretability

Select all answers that apply