決定樹を習う

The key problem of gradient boosting is that you must maintain N decision trees to sum over, so rather than keeping only a single tree's root node in a data structure, multiple trees must remembered. The trees are summed in each inference, where tree i's output was trained based on the residual of the sum of the first i-1 trees' outputs and the expected output.