Random forest
In supervised learning, overfitting is a major problem. When it comes to regression trees, it becomes more obvious to prevent this, we specify the Seth of the tree, but there is still a high chance of the dataset being overfitted. To avoid this, we use a random first regressor. Before understanding how and why this … Read more