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Abstract:TF Boosted Trees (TFBT) is a new open-sourced frame-work for the distributed training of gradient boosted trees. It is based on TensorFlow, and its distinguishing features include a novel architecture, automatic loss differentiation, layer-by-layer boosting that results in smaller ensembles and faster prediction, principled multi-class handling, and a number of regularization techniques to prevent overfitting.
* European Conference on Machine Learning and Principles and Practice
of Knowledge Discovery in Databases (ECML PKDD 2017). The final publication
will be available at link.springer.com and is available on ECML website
http://ecmlpkdd2017.ijs.si/papers/paperID705.pdf