arXiv (Cornell University)· 2018· Preprint
CatBoost: gradient boosting with categorical features support
- 1,354citations
- 2018year
Short summary
CatBoost is a new open-source gradient boosting library that handles categorical features and outperforms existing implementations on public datasets.
AI-generated from the title and abstract; the full text is not read.
TakeawaysIn the app
Key pointsIn the app
Ask the paperIn the app
The rest is in the Pofolia app
Takeaways, key points and questions to the paper; new summaries every day for your field. Free.
Sign in on the web to openField: Signal Processing
Signal ProcessingComputer Science