CatBoost¶
Prokhorenkova, L., Gusev, G., Vorobev, A., Dorogush, A. V., & Gulin, A. (2018). CatBoost: Unbiased Boosting with Categorical Features. Advances in Neural Information Processing Systems, 31.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Categorical Encoding Scheme
- Its signature failure is target leakage through mean encoding: computed in-sample, the encoded value contains the row's own label, producing spectacular offline scores that vanish in production.
This sourceShows that ordinary in-sample categorical target statistics can incorporate an observation's own label, causing target leakage.
- Its signature failure is target leakage through mean encoding: computed in-sample, the encoded value contains the row's own label, producing spectacular offline scores that vanish in production.
Verification¶
Does it exist? Not checked yet. This entry carries no identifier to resolve. It was extracted from the citation as written in the article, normalized, and deduplicated against the rest of the registry.
Does it back the claim? Not recorded. The single citation of this work carries no recorded support check.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Registry ID ref:73de7841cbe2 · see in the full table