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The Ethereal
TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting
October 31, 2017 ยท Declared Dead ยท ๐ ECML/PKDD
"No code URL or promise found in abstract"
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Authors
Natalia Ponomareva, Soroush Radpour, Gilbert Hendry, Salem Haykal, Thomas Colthurst, Petr Mitrichev, Alexander Grushetsky
arXiv ID
1710.11555
Category
stat.ML: Machine Learning (Stat)
Cross-listed
cs.LG
Citations
24
Venue
ECML/PKDD
Last Checked
4 months ago
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.
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