Practice Disadvantages (7.2.5) - Ensemble Methods – Bagging, Boosting, and Stacking

Practice: Disadvantages

Lesson 7.2.5Ensemble Methods – Bagging, Boosting, and Stacking

Practise this section

8 questions

Flashcard drill
2 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
Sign up to start the exercise
Quiz
2 questions · about 1 min · pass mark 70%. Hints available.
Sign up to start the quiz

6 sample questions

Question 1.
What is one disadvantage of bagging?
Show hintHide hint
Think about what bagging helps to reduce.
Question 2.
How does bagging affect computational time?
Show hintHide hint
Consider how many models are trained in this process.
3Question 3.
Bagging is particularly effective for high-variance models.
- True
- False
Show hintHide hint
Think about the type of models bagging is used with.
4Question 4.
What is the primary disadvantage of bagging?
- It increases bias
- It requires training multiple models
- It only works with specific algorithms
Show hintHide hint
Consider the process of how many models are created.
Question 5.
If you are tasked with improving a highly biased model, results have shown poor performance. Would bagging be the suitable technique? Justify your reasoning.
Show hintHide hint
Reflect on what biases mean in terms of model performance.
Question 6.
Imagine you have scalable computing resources, but time is tight. Discuss how bagging might fit into your model training process and the benefits or drawbacks it could entail.
Show hintHide hint
Consider the trade-off between time and accuracy.

4 more questions in this section. Enroll free to practise them all.