Highlights:
- ETNA native RNN and base classes for deep learning models
- Lambda transform
- Prophet 1.1 support without c++ compiler dependency
- Prediction intervals for DeepAR and TFTModel
- Add
known_future
parameter to CLI
Full changelog:
Added
- LSTM based RNN and native deep models base classes (#776)
- Lambda transform (#762)
- assemble pipelines (#774)
- Tests on in-sample, out-sample predictions with gap for all models (#785)
Changed
- Add columns and mode parameters in plot_correlation_matrix (#726)
- Add CatBoostPerSegmentModel and CatBoostMultiSegmentModel classes, deprecate CatBoostModelPerSegment and CatBoostModelMultiSegment (#779)
- Allow Prophet update to 1.1 (#799)
- Make LagTransform, LogTransform, AddConstTransform vectorized (#756)
- Improve the behavior of plot_feature_relevance visualizing p-values (#795)
- Update poetry.core version (#780)
- Make native prediction intervals for DeepAR (#761)
- Make native prediction intervals for TFTModel (#770)
- Test cases for testing inference of models (#794)
- Wandb.log to WandbLogger (#816)
Fixed
- Fix missing prophet in docker images (#767)
- Add
known_future
parameter to CLI (#758) - FutureWarning: The frame.append method is deprecated. Use pandas.concat instead (#764)
- Correct ordering if multi-index in backtest (#771)
- Raise errors in models.nn if they can't make in-sample and some cases out-sample predictions (#813)
- Teach BATS/TBATS to work with in-sample, out-sample predictions correctly (#806)
- Github actions cache issue with poetry update (#778)