3 Key Differences Between Random Forests and GBDT

Random forest and gradient boosted decision trees (GBDT) are the two most commonly used machine learning algorithms. Both are ensemble models which means they combine many weak learners to get a strong one. Although both random forest and GBDT use the same weak learner, they are highly different algorithms. In this article, we will focus on 3 key differences between these ensemble techniques. Decision trees are used as the weak learner in both algorithms.