✅ Quiz M6.01

✅ 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