Asked about Learning a mapping from examples
Why do gradient boosted trees still beat neural networks on tabular data?
An answer that works
Tabular features are heterogeneous and many are uninformative, and trees select among them rather than having to learn to ignore. Trees are also invariant to feature scaling, handle missing values natively, and work on the smaller datasets typical of tabular problems.
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