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Changelog

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.

[0.4.3] - 2020-xx-xx

[0.4.2] - 2020-10-01

Added

  • 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

Fixed

  • Documentation fixes (#400) @brettkoonce, (#399) @akanz1, (#404) @alwinw

Changed

  • 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

[0.4.1] - 2020-07-09

Added

  • 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

Changed

  • Replaced gunpoint dataset in tutorials, added OSULeaf dataset (#295) @marielledado
  • Updated macOS advanced install instructions (#306) (#308) @sophijka
  • Updated contributing guidelines (#301) @Ayushmaanseth

Fixed

  • 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

[0.4.0] - 2020-06-05

Added

  • 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

Changed

  • Revised all estimators to comply with common interface and to ensure scikit-learn compatibility

Removed

  • A few redundant classes for the series-as-features setting in favour of scikit-learn's implementations: Pipeline and GridSearchCV
  • HomogeneousColumnEnsembleClassifier in favour of more flexible ColumnEnsembleClassifier

Fixed

  • Deprecation and future warnings from scikit-learn
  • User warnings from statsmodels