Econml

This is a major update of the library, with several important improvements, as well as a number of bug-fixes and minor improvements.

What's Changed

* Adds the ability to scale ortholearner training using Ray (by v-shaal in https://github.com/py-why/EconML/pull/800)
* Allows missing values in W and sometimes X (by fverac in https://github.com/py-why/EconML/pull/791)
* Enables federated estimation of linear models (by kgao in https://github.com/py-why/EconML/pull/818)
* Provides a CATE validation suite for discrete models (by amarvenu in https://github.com/py-why/EconML/pull/777 and https://github.com/py-why/EconML/pull/836)
* Enable model selection for first stage models (by kbattocchi in https://github.com/py-why/EconML/pull/808 and https://github.com/py-why/EconML/pull/848)
* Improve discreteness handling, allow binary outcomes by fverac in https://github.com/py-why/EconML/pull/816

New Contributors
* star1327p made their first contribution in https://github.com/py-why/EconML/pull/713
* v-shaal made their first contribution in https://github.com/py-why/EconML/pull/800
* kgao made their first contribution in https://github.com/py-why/EconML/pull/818
* amarvenu made their first contribution in https://github.com/py-why/EconML/pull/777

**Full Changelog**: https://github.com/py-why/EconML/compare/v0.14.1...v0.15.0

What's Changed

This beta has many bug fixes and provides several big improvements:
* Adds the ability to scale ortholearner training using Ray (by v-shaal in https://github.com/py-why/EconML/pull/800)
* Allows missing values in W and sometimes X (by fverac in https://github.com/py-why/EconML/pull/791)
* Enables federated estimation of linear models (by kgao in https://github.com/py-why/EconML/pull/818)
* Provides a CATE validation suite for discrete models (by amarvenu in https://github.com/py-why/EconML/pull/777)
* Enable model selection for first stage models (by kbattocchi in https://github.com/py-why/EconML/pull/808)

New Contributors
* v-shaal made their first contribution in https://github.com/py-why/EconML/pull/800
* kgao made their first contribution in https://github.com/py-why/EconML/pull/818

**Full Changelog**: https://github.com/py-why/EconML/compare/v0.14.1...v0.15.0b1

What's Changed

Details

Minor updates and bugfixes
* Avoid returning defaultdict directly when calling `est.shap_values` kbattocchi in https://github.com/py-why/EconML/pull/709
* Refactor `DynamicDML` to remove incompatible method signatures by kbattocchi in https://github.com/py-why/EconML/pull/717
* Fix bug when using .`score` in _OrthoLearner subclasses by kbattocchi in https://github.com/py-why/EconML/issues/760

Package changes
* Enable sklearn 1.2 by 00helloworld and kbattocchi in https://github.com/py-why/EconML/pull/712
* Enable compatibility with pandas 2.0 by kbattocchi in https://github.com/py-why/EconML/pull/750
* Fix numpy 1.24 compatibility by kbattocchi in https://github.com/py-why/EconML/pull/750
* Bump supported shap version limit by kbattocchi in https://github.com/py-why/EconML/pull/750

Build system changes
* Enable GitHub Actions by kbattocchi in https://github.com/py-why/EconML/pull/746
* Use verbose pip install when debugging workflows by kbattocchi in https://github.com/py-why/EconML/pull/746
* Update developer documentation by kbattocchi in https://github.com/py-why/EconML/pull/749

Misc
* Update copyrights and references to point to PyWhy by kbattocchi in https://github.com/py-why/EconML/pull/749
* Updated CI badge in README by kbattocchi and fverac https://github.com/py-why/EconML/pull/771

**Full Changelog**: https://github.com/py-why/EconML/compare/v0.14.0...v0.14.1

What's Changed
This release contains a major new feature, treatment featurization (615), plus a number of bugfixes and minor improvements.

**Breaking changes**: several deprecated features have now been removed, and DynamicDML has been moved to a new `econml.panel` package.

Details

Major changes
* treatment featurization by fverac in https://github.com/microsoft/EconML/pull/615
* Create panel subpackage by kbattocchi in https://github.com/microsoft/EconML/pull/662
* Remove deprecated functionality by kbattocchi in https://github.com/microsoft/EconML/pull/663

Minor updates and bugfixes
* fix small typo by Padarn in https://github.com/microsoft/EconML/pull/651
* initial commit for aka.ms/econml doc migration by fverac in https://github.com/microsoft/EconML/pull/640
* Update README.md by coreynoone in https://github.com/microsoft/EconML/pull/658
* add usage examples in docs for backdoor and IV methods, add KernelDML to docs by fverac in https://github.com/microsoft/EconML/pull/677
* Update Policy Learning with Trees and Forests.ipynb by OliverTseng in https://github.com/microsoft/EconML/pull/685

Package changes
* Remove dowhy as core dependency by kbattocchi in https://github.com/microsoft/EconML/pull/661
* add matplotlib version ceiling by fverac in https://github.com/microsoft/EconML/pull/680

Build system changes
* update some pipeline images (macos-12, ubuntu20), fix pycodestyle E275 by fverac in https://github.com/microsoft/EconML/pull/672

New Contributors
* Padarn made their first contribution in https://github.com/microsoft/EconML/pull/651
* coreynoone made their first contribution in https://github.com/microsoft/EconML/pull/658
* OliverTseng made their first contribution in https://github.com/microsoft/EconML/pull/685

**Full Changelog**: https://github.com/microsoft/EconML/compare/v0.13.1...v0.14.0

What's Changed
This is a minor release which mainly fixes several minor bugs and compatibility issues with certain versions of other libraries such as dowhy and sklearn.

Details:
Bug fixes
* improve input processing for StatsModelsLinearRegression by fverac in https://github.com/microsoft/EconML/pull/599
* Fix RScorer circular import by fverac in https://github.com/microsoft/EconML/pull/596
* Docs - typos in dr.rst by stanton119 in https://github.com/microsoft/EconML/pull/603
* Fix small issues by kbattocchi in https://github.com/microsoft/EconML/pull/617
* Fix typo in motivation docs by imatiach-msft in https://github.com/microsoft/EconML/pull/624
* Another minor typo fix in docs by imatiach-msft in https://github.com/microsoft/EconML/pull/625
* Replace Boston housing analysis with Ames housing by fverac in https://github.com/microsoft/EconML/pull/598
* Several small fixes by kbattocchi in https://github.com/microsoft/EconML/pull/629
* Handle pandas categorical types for categorical columns in _causal_analysis.py by gaugup in https://github.com/microsoft/EconML/pull/602
* fix a typo by zjyfdu in https://github.com/microsoft/EconML/pull/636
* fix _preprocess_data to align with sklearn refactor by fverac in https://github.com/microsoft/EconML/pull/638
* Fix RScorer circular import by fverac in https://github.com/microsoft/EconML/pull/596
* Docs - typos in dr.rst by stanton119 in https://github.com/microsoft/EconML/pull/603

Compatibility changes
* updates dependency dowhy to v0.7 by xrowan in https://github.com/microsoft/EconML/pull/568
* upgrade econml to latest version of shap by imatiach-msft in https://github.com/microsoft/EconML/pull/595
* Fix support for sklearn<1.0 by kbattocchi in https://github.com/microsoft/EconML/pull/637

Build system improvements
* Profiling Unit Tests by xrowan in https://github.com/microsoft/EconML/pull/575
* Disable serial tests on macOS by kbattocchi in https://github.com/microsoft/EconML/pull/604
* Adding Microsoft SECURITY.MD by microsoft-github-policy-service in https://github.com/microsoft/EconML/pull/622


**Full Changelog**: https://github.com/microsoft/EconML/compare/v0.13.0...v0.13.1

This release enables support for Python 3.9 and sklearn 1.0 and improves the documentation of the OrthoIV and DRIV classes.

Note that for the moment, the Python 3.9 version of econml does not support the deepiv module because of conflicts with our required versions of tensorflow and keras; we hope to address this in a subsequent release.

What's Changed
* Add notebook for DRIV by heimengqi in https://github.com/microsoft/EconML/pull/518

**Full Changelog**: https://github.com/microsoft/EconML/compare/v0.12.0...v0.13.0