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Extra boosting algorithm on tensorflow
I have read your paper, and it is great one. Is it possible to have clearly annotated examples how to use the package with its various options?
I am not sure how difficult it would be to implement this. Is it possible to add a feature that would allow one to regress in the leaves only on a subset of features? E.g. if we have 3 features f1, f2, f3, the xgb trees are constructed by using features f1, f2 (or all of them) but the linear regression is done on features f2, f3 (notice the overlap).
Thanks.
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