MagicBricks Jr. Data Scientist Interview Questions and Answers

Trees bagging and boosting are ensemble learning techniques that use multiple decision trees, but with different approaches.

• Bagging (Bootstrap Aggregating) involves training multiple decision trees independently on different subsets of the training data and then averaging the predictions. Examples include Random Forest.

• Boosting involves training multiple decision trees sequentially, with each tree correcting the errors...read more