All notable changes to this project will be documented in this file. We keep track of changes in this file since v0.4.0. The format is based on Keep a Changelog and we adhere to Semantic Versioning. The source code for all releases is available on GitHub.
- Exclude Python 3.10 from manylinux CI (#870) @mloning
- Fix AutoETS handling of infinite information criteria (#848) @ltsaprounis
- Fix smape import (#851) @mloning
- ThetaForecaster now works with initial_level (#769) @yashlamba
- Use joblib to parallelize ensemble fitting for Rocket classifier (#796) @kachayev
- Update maintenance tools (#829) @mloning
- Undo pmdarima hotfix and avoid pmdarima 1.8.1 (#831) @aaronreidsmith
- Hotfix pmdarima version (#828) @aiwalter
- Added Guerrero method for lambda estimation to BoxCoxTransformer (#778) (#791) @GuzalBulatova
- New forecasting metrics (#801) @RNKuhns
- Implementation of DirRec reduction strategy (#779) @luiszugasti
- Added cutoff to BaseGridSearch to use any grid search inside evaluate… (#825) @aiwalter
- Added pd.DataFrame transformation for Imputer and HampelFilter (#830) @aiwalter
- Added default params for some transformers (#834) @aiwalter
- Added several docstring examples (#835) @aiwalter
- Added skip-inverse-transform tag for Imputer and HampelFilter (#788) @aiwalter
- Added a reference to alibi-detect (#815) @satya-pattnaik
All contributors: @GuzalBulatova, @RNKuhns, @aaronreidsmith, @aiwalter, @kachayev, @ltsaprounis, @luiszugasti, @mloning, @satya-pattnaik and @yashlamba
- Fix counting for Github's automatic language discovery (#812) @xuyxu
- Fix counting for Github's automatic language discovery (#811) @xuyxu
- Fix examples CI checks (#793) @mloning
- Fix TimeSeriesForestRegressor (#777) @mloning
- Fix Deseasonalizer docstring (#737) @mloning
- SettingWithCopyWarning in Prophet with exogenous data (#735) @jschemm
- Correct docstrings for check_X and related functions (#701) @Lovkush-A
- Fixed bugs mentioned in #694 (#697) @AidenRushbrooke
- fix typo in CONTRIBUTING.md (#688) @luiszugasti
- Fix duplicacy in the contribution's list (#685) @afzal442
- HIVE-COTE 1.0 fix (#678) @MatthewMiddlehurst
- Update sklearn version (#810) @mloning
- Remove soft dependency check for numba (#808) @mloning
- Modify tests for forecasting reductions (#756) @Lovkush-A
- Upgrade nbqa (#794) @MarcoGorelli
- Enhanced exception message of splitters (#771) @aiwalter
- Enhance forecasting model selection/evaluation (#739) @mloning
- Pin PyStan version (#751) @mloning
- master to main conversion in docs folder closes #644 (#667) @ayan-biswas0412
- Update governance (#686) @mloning
- remove MSM from unit tests for now (#698) @TonyBagnall
- Make update_params=true by default (#660) @pabworks
- update dataset names (#676) @TonyBagnall
- Add support for exogenous variables to forecasting reduction (#757) @mloning
- Added forecasting docstring examples (#772) @aiwalter
- Added the agg argument to EnsembleForecaster (#774) @Ifeanyi30
- Added OptionalPassthrough transformer (#762) @aiwalter
- Add doctests (#766) @mloning
- Multiplexer forecaster (#715) @koralturkk
- Upload source tarball to PyPI during releases (#749) @dsherry
- Create developer guide (#734) @mloning
- Refactor TSF classifier into TSF regressor (#693) @luiszugasti
- Outlier detection with HampelFilter (#708) @aiwalter
- changes to contributing.md to include directions to installation (#695) @kanand77
- Evaluate (example and fix) (#690) @aiwalter
- Knn unit tests (#705) @TonyBagnall
- Knn transpose fix (#689) @TonyBagnall
- Evaluate forecaster function (#657) @aiwalter
- Multioutput reduction strategy for forecasting (#659) @Lovkush-A
All contributors: @AidenRushbrooke, @Ifeanyi30, @Lovkush-A, @MarcoGorelli, @MatthewMiddlehurst, @TonyBagnall, @afzal442, @aiwalter, @ayan-biswas0412, @dsherry, @jschemm, @kanand77, @koralturkk, @luiszugasti, @mloning, @pabworks and @xuyxu
- Fix reduced regression forecaster reference (#658) @mloning
- Address Bug #640 (#642) @patrickzib
- Ed knn (#638) @TonyBagnall
- Euclidean distance for KNNs (#636) @goastler
- Pin NumPy 1.19 (#643) @mloning
- Update CoC committee (#614) @mloning
- Benchmarking issue141 (#492) @ViktorKaz
- Catch22 Refactor & Multithreading (#615) @MatthewMiddlehurst
- Create new factory method for forecasting via reduction (#635) @Lovkush-A
- Feature ForecastingRandomizedSearchCV (#634) @pabworks
- Added Imputer for missing values (#637) @aiwalter
- Add expanding window splitter (#627) @koralturkk
- Forecasting User Guide (#595) @Lovkush-A
- Add data processing functionality to convert between data formats (#553) @RNKuhns
- Add basic parallel support for ElasticEnsemble (#546) @xuyxu
All contributors: @Lovkush-A, @MatthewMiddlehurst, @RNKuhns, @TonyBagnall, @ViktorKaz, @aiwalter, @goastler, @koralturkk, @mloning, @pabworks, @patrickzib and @xuyxu
- Fix ModuleNotFoundError issue (#613) @Hephaest
- Fixes _fit(X) in KNN (#610) @TonyBagnall
- UEA TSC module improvements 2 (#599) @TonyBagnall
- Fix sktime.classification.frequency_based not found error (#606) @Hephaest
- UEA TSC module improvements 1 (#579) @TonyBagnall
- Relax numba pinning (#593) @dhirschfeld
- Fix fh.to_relative() bug for DatetimeIndex (#582) @aiwalter
All contributors: @Hephaest, @MatthewMiddlehurst, @TonyBagnall, @aiwalter and @dhirschfeld
- Add ARIMA (#559) @HYang1996
- Add fbprophet wrapper (#515) @aiwalter
- Add MiniRocket and MiniRocketMultivariate (#542) @angus924
- Add Cosine, ACF and PACF transformers (#509) @afzal442
- Add example notebook Window Splitters (#555) @juanitorduz
- Add SlidingWindowSplitter visualization on doctrings (#554) @juanitorduz
- Pin pandas version to fix pandas-related AutoETS error on Linux (#581) @mloning
- Fixed default argument in docstring in SlidingWindowSplitter (#556) @ngupta23
All contributors: @HYang1996, @TonyBagnall, @afzal442, @aiwalter, @angus924, @juanitorduz, @mloning and @ngupta23
- Add tests for forecasting with exogenous variables (#547) @mloning
- Add HCrystalBall wrapper (#485) @MichalChromcak
- Tbats (#527) @aiwalter
- Added matrix profile using stumpy (#471) @utsavcoding
- User guide (#377) @mloning
- Add GitHub workflow for building and testing on macOS (#505) @mloning
- [DOC] Add dtaidistance (#502) @mloning
- Implement the feature_importances_ property for RISE (#497) @AaronX121
- Add scikit-fda to the list of related software (#495) @vnmabus
- [DOC] Add roadmap to docs (#467) @mloning
- Add parallelization for RandomIntervalSpectralForest (#482) @AaronX121
- New Ensemble Forecasting Methods (#333) @magittan
- CI run black formatter on notebooks as well as Python scripts (#437) @MarcoGorelli
- Implementation of catch22 transformer, CIF classifier and dictionary based clean-up (#453) @MatthewMiddlehurst
- Added write dataset to ts file functionality (#438) @whackteachers
- Added ability to load from csv containing long-formatted data (#442) @AidenRushbrooke
- Transform typing (#420) @mloning
- Refactoring utils and transformer module (#538) @mloning
- Update README (#454) @mloning
- Clean up example notebooks (#548) @mloning
- Update README.rst (#536) @aiwalter
- [Doc]Updated load_data.py (#496) @Afzal-Ind
- Update forecasting.py (#487) @raishubham1
- update basic motion description (#475) @vollmersj
- [DOC] Update docs in benchmarking/data.py (#489) @Afzal-Ind
- Edit Jupyter Notebook 01_forecasting (#486) @bmurdata
- Feature & Performance improvements of SFA/WEASEL (#457) @patrickzib
- Moved related software from wiki to docs (#439) @mloning
- Fixed issue outlined in issue 522 (#537) @ngupta23
- Fix plot-series (#533) @gracewgao
- added mape_loss and cosmetic fixes to notebooks (removed kernel) (#500) @tch
- Fix azure pipelines (#506) @mloning
- [DOC] Fix broken docstrings of RandomIntervalSpectralForest (#473) @AaronX121
- Add back missing bibtex reference to classifiers (#468) @whackteachers
- Avoid seaborn warning (#472) @davidbp
- Bump pre-commit versions, run again on notebooks (#469) @MarcoGorelli
- Fix series validation (#463) @mloning
- Fix soft dependency imports (#446) @mloning
- Fix bug in AutoETS (#445) @HYang1996
- Add ForecastingHorizon class to docs (#444) @mloning
- Remove manylinux1 (#458) @mloning
All contributors: @AaronX121, @Afzal-Ind, @AidenRushbrooke, @HYang1996, @MarcoGorelli, @MatthewMiddlehurst, @MichalChromcak, @TonyBagnall, @aiwalter, @bmurdata, @davidbp, @gracewgao, @magittan, @mloning, @ngupta23, @patrickzib, @raishubham1, @tch, @utsavcoding, @vnmabus, @vollmersj and @whackteachers
- Support for 3d numpy array (#405) @mloning
- Support for downloading dataset from UCR UEA time series classification data set repository (#430) @Emiliathewolf
- Univariate time series regression example to TSFresh notebook (#428) @evanmiller29
- Parallelized TimeSeriesForest using joblib. (#408) @kkoziara
- Unit test for multi-processing (#414) @kkoziara
- Add date-time support for forecasting framework (#392) @mloning
- Performance improvements of dictionary classifiers (#398) @patrickzib
- Fix links in Readthedocs and Binder launch button (#416)
@mloning * Fixed small bug in performance metrics (#422) @krumeto * Resolved warnings in notebook examples (#418) @alwinw * Resolves #325 ModuleNotFoundError for soft dependencies (#410) @alwinw
All contributors: @Emiliathewolf, @alwinw, @evanmiller29, @kkoziara, @krumeto, @mloning and @patrickzib
- ETSModel with auto-fitting capability (#393) @HYang1996
- WEASEL classifier (#391) @patrickzib
- Full support for exogenous data in forecasting framework (#382) @mloning, (#380) @mloning
- Multivariate dataset for US consumption over time (#385) @SebasKoel
- Governance document (#324) @mloning, @fkiraly
- Documentation fixes (#400) @brettkoonce, (#399) @akanz1, (#404) @alwinw
- Move documentation to ReadTheDocs with support for versioned documentation (#395) @mloning
- Refactored SFA implementation (additional features and speed improvements) (#389) @patrickzib
- Move prediction interval API to base classes in forecasting framework (#387) @big-o
- Documentation improvements (#364) @mloning
- Update CI and maintenance tools (#394) @mloning
All contributors: @HYang1996, @SebasKoel, @fkiraly, @akanz1, @alwinw, @big-o, @brettkoonce, @mloning, @patrickzib
- New sktime logo @mloning
- TemporalDictionaryEnsemble (#292) @MatthewMiddlehurst
- ShapeDTW (#287) @Multivin12
- Updated sktime artwork (logo) @mloning
- Truncation transformer (#315) @ABostrom
- Padding transformer (#316) @ABostrom
- Example notebook with feature importance graph for time series forest (#319) @HYang1996
- ACSF1 data set (#314) @BandaSaiTejaReddy
- Data conversion function from 3d numpy array to nested pandas dataframe (#304) @vedazeren
- Replaced gunpoint dataset in tutorials, added OSULeaf dataset (#295) @marielledado
- Updated macOS advanced install instructions (#306) (#308) @sophijka
- Updated contributing guidelines (#301) @Ayushmaanseth
- Typos (#293) @Mo-Saif, (#285) @Pangoraw, (#305) @hiqbal2
- Manylinux wheel building (#286) @mloning
- KNN compatibility with sklearn (#310) @Cheukting
- Docstrings for AutoARIMA (#307) @btrtts
All contributors: @Ayushmaanseth, @Mo-Saif, @Pangoraw, @marielledado, @mloning, @sophijka, @Cheukting, @MatthewMiddlehurst, @Multivin12, @ABostrom, @HYang1996, @BandaSaiTejaReddy, @vedazeren, @hiqbal2, @btrtts
- Forecasting framework, including: forecasting algorithms (forecasters), tools for composite model building (meta-forecasters), tuning and model evaluation
- Consistent unit testing of all estimators
- Consistent input checks
- Enforced PEP8 linting via flake8
- Changelog
- Support for Python 3.8
- Support for manylinux wheels
- Revised all estimators to comply with common interface and to ensure scikit-learn compatibility
- A few redundant classes for the series-as-features setting in favour of scikit-learn's implementations:
Pipeline
andGridSearchCV
HomogeneousColumnEnsembleClassifier
in favour of more flexibleColumnEnsembleClassifier
- Deprecation and future warnings from scikit-learn
- User warnings from statsmodels