Known limitations

• Windows is not supported. Work in progress.
• GPU is not supported. Work in progress.
• Text and embeddings features are not supported. Work in progress.
• Feature distribution statistics (like calc_feature_statisticson CatBoost python package) with datasets on Spark is not supported. But it is possible to run such analysis with models exported to local files in usual CatBoost format.
• Generic string class labels are not supported. String class labels can be used only if these strings represent integer indices.
• boosting_type=Ordered is not supported.
• Training of models with non-symmetric trees is not supported. But such models can be loaded and applied on datasets in Spark.
• Monotone constraints are not supported.
• Multitarget training is not supported.
• Stochastic Gradient Langevin Boosting mode is not supported.