Ensemble Learning QUIZ - MCQ QUESTIONS AND ANSWERS

Question: 1

What is an ensemble learning model?

Question: 2

What is bagging in ensemble learning?

Question: 3

What is the purpose of the AdaBoost algorithm in ensemble learning?

Question: 4

What is ensemble learning?

Question: 5

What is an ensemble model?

Question: 6

What is a base learner?

Question: 7

What is bagging?

Question: 8

What is boosting?

Question: 9

What is the difference between bagging and boosting?

Question: 10

What is the purpose of cross-validation in ensemble learning?

Question: 11

What is a random forest?

Question: 12

What is the difference between bagging and random forests?

Question: 13

What is AdaBoost?

Question: 14

What is gradient boosting?

Question: 15

What is XGBoost?

Question: 16

What is stacking?

Question: 17

What is the difference between a homogeneous and a heterogeneous ensemble?

Question: 18

What is a committee machine?

Question: 19

What is a model averaging ensemble?

Question: 20

What is a bagging ensemble?

Question: 21

What is a boosting ensemble?

Question: 22

What is the difference between random forests and bagging?

Question: 23

What is the difference between bagging and pasting?

Question: 24

What is the purpose of the Out-of-Bag (OOB) error in a bagging ensemble?

Question: 25

What is a learning curve in the context of ensemble learning?

Question: 26

What is stacking in ensemble learning?

Question: 27

Which of the following is NOT a type of ensemble learning?

Question: 28

What is the difference between homogeneous and heterogeneous ensembles?

Question: 29

What is the purpose of early stopping in gradient boosting?

Question: 30

Which of the following is a disadvantage of using boosting for ensemble learning?