9e9f0ffc3d836836ca96cbf8fe14b105-Supplemental-Conference.pdf

Inanutshell, features ofthis dataset are sampled randomly fromN(0,1), and the target is produced by an ensemble of randomly constructed decision trees applied to the sampledfeatures. Our dataset has10,000 objects, 8 features and the target was produced by16 decision trees of depth6. CatBoost is trained with the default hyperparameters. Importantly,thelattermeans that this approach is not covered by the embedding framework described in subsection 3.1. So, it seems to be important to embed each feature separately as describedinsubsection3.1.