Introduction CatBoost is an open-sourced gradient boosting library that natively handles categorical features and performs well in comparison to existing publicly available implementations of gradient boosting such as XGBoost, LightGBM and H2O. [1] In this article we present the details of CatBoost’s ordered target-based statistic (ordered TBS), its analytical solution when number of permutations approaches…