Editing Bootstrap aggregating (section)

=== Application ===
Creating the bootstrap and out-of-bag datasets is crucial since it is used to test the accuracy of [[ensemble learning]] algorithms like [[random forest]]. For example, a model that produces 50 trees using the bootstrap/out-of-bag datasets will have a better accuracy than if it produced 10 trees. Since the algorithm generates multiple trees and therefore multiple datasets the chance that an object is left out of the bootstrap dataset is low. The next few sections talk about how the random forest algorithm works in more detail.