The random forest (RF) model is a modification to what algorithm?
A) complex bagging
B) simple bagging
C) complex boosting
D) simple boosting

Question

Quizplus · Accepted Answer

The random forest model is a modification of the simple bagging algorithm, where decision trees are used as the base learners. Bagging, or Bootstrap Aggregating, involves training multiple models in parallel on bootstrapped subsets of the data and then aggregating their predictions. Random forests enhance this approach by also incorporating feature randomness when splitting nodes, thus improving model variance and preventing overfitting.

The Random Forest (RF) Model Is a Modification to What