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from the catboost page there's also a link to this: Fighting biases with dynamic boosting - Dorogush, Gulin, Gusev, Kazeev, Prokhorenkova, Vorobev https://arx
by shoo 9y ago
from the catboost page there's also a link to this:
Fighting biases with dynamic boosting - Dorogush, Gulin, Gusev, Kazeev, Prokhorenkova, Vorobev
https://arxiv.org/pdf/1706.09516.pdf https://arxiv.org/pdf/1706.09516.pdf
> While gradient boosting algorithms are the workhorse of modern industrial machine learning and data science, all current implementations are susceptible to a non-trivial but damaging form of label leakage. It results in a systematic bias in pointwise gradient estimates that lead to reduced accuracy
- cropsieboss 9y agoI was thinking of this one: https://arxiv.org/pdf/1706.01109.pdf https://arxiv.org/pdf/1706.01109.pdf I see a github link in there https://github.com/arogozhnikov/infiniteboost https://github.com/arogozhnikov/infiniteboost, but it does not seem to be in CatBoost (as someone here pointed out better logloss has to do with CatBoost handling of categorical features).