Which of the Following Is a Fundamental Difference Between Bagging

Multiple Choice

Which of the following is a fundamental difference between bagging and boosting?

A) Bagging is used for supervised learning. Boosting is used with unsupervised clustering.
B) Bagging gives varying weights to training instances. Boosting gives equal weight to all training instances.
C) Bagging does not take the performance of previously built models into account when building a new model. With boosting each new model is built based upon the results of previous models.
D) With boosting, each model has an equal weight in the classification of new instances. With bagging, individual models are given varying weights.