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Compact Multi-Class Boosted Trees
[article]
2017
arXiv
pre-print
Gradient boosted decision trees are a popular machine learning technique, in part because of their ability to give good accuracy with small models. We describe two extensions to the standard tree boosting algorithm designed to increase this advantage. The first improvement extends the boosting formalism from scalar-valued trees to vector-valued trees. This allows individual trees to be used as multiclass classifiers, rather than requiring one tree per class, and drastically reduces the model
arXiv:1710.11547v1
fatcat:e23td22nwvdmpl5e2jwfz6etva