✅ Quiz M6.01

Question

By default, a BaggingClassifier or BaggingRegressor draw:

• a) random samples with replacement over training points

• b) random samples with replacement over features

• c) random samples without replacement over training points

• d) random samples without replacement over features

Select all answers that apply

Hint: it is possible to access the documentation for those classes by clicking on the links on their names.

Question

In a BaggingClassifier or BaggingRegressor, the parameter base_estimator can be:

• a) any predictor

• b) a decision tree predictor

• c) a linear model predictor

Select a single answer

Question

In the context of a classification problem, what are the differences between a bagging classifier and a random forest classifier:

• a) in a random forest, the base model is always a decision tree

• b) in a random forest, the split threshold values are decided completely at random

• c) in a random forest, a random resampling is performed both over features as well as over samples

Select all answers that apply