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Document limitation of one-split-at-a-time Greedy tree learning heuristic #4233

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Mar 8, 2019
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Document limitation of one-split-at-a-time Greedy tree learning heuristic #4233

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4 changes: 4 additions & 0 deletions doc/tutorials/model.rst
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Expand Up @@ -255,6 +255,10 @@ For real valued data, we usually want to search for an optimal split. To efficie

A left to right scan is sufficient to calculate the structure score of all possible split solutions, and we can find the best split efficiently.

.. note:: Limitation of additive tree learning

Since it is intractable to enumerate all possible tree structures, we add one split at a time. This approach works well most of the time, but there are some edge cases that fail due to this approach. For those edge cases, training results in a degenerate model because we consider only one feature dimension at a time. See `Can Gradient Boosting Learn Simple Arithmetic? <http://mariofilho.com/can-gradient-boosting-learn-simple-arithmetic/>`_ for an example.

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Final words on XGBoost
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