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=Orderedis 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.