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This paper presents the key algorithmic techniques behind CatBoost, a new gradient boosting toolkit. Their combination leads to CatBoost outperforming other publicly available boosting… (More)
In this paper we present CatBoost, a new open-sourced gradient boosting library that successfully handles categorical features and outperforms existing publicly available implementations of gradient… (More)
While gradient boosting algorithms are the workhorse of modern industrial machine learning and data science, all current implementations are susceptible to a nontrivial but damaging form of label… (More)
This article provides a comprehensive study of different ways to make speed benchmarks of gradient boosted decision trees algorithm. We show main problems of several straight forward ways to make… (More)