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Releases: py-why/EconML

v0.15.1

04 Jul 19:00
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This is a bugfix release which contains a number of small improvements to the 0.15.0 release.

What's Changed

  • Fix needs_fit logic for model selection with a fixed model by @kbattocchi in #855
  • CATE validation - uplift uniform confidence bands by @amarvenu in #840
  • Typo fixes by @alexmalins in #864
  • Fix shap_values compatibility with shap>=0.43.0 by adjusting check_additivity parameter handling for TreeExplainer by @jcreinhold in #872
  • Optimizing NormalInferenceResults confidence interval method speed by @gdaiha in #879
  • Enable scikit-learn 1.5 compatibility by @kbattocchi in #891
  • A number of improvements to our infrastructure (#861, #863, #867, #876, #880, #882)

New Contributors

Full Changelog: v0.15.0...v0.15.1

v0.15.0

27 Feb 17:42
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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 #800)
  • Allows missing values in W and sometimes X (by @fverac in #791)
  • Enables federated estimation of linear models (by @kgao in #818)
  • Provides a CATE validation suite for discrete models (by @amarvenu in #777 and #836)
  • Enable model selection for first stage models (by @kbattocchi in #808 and #848)
  • Improve discreteness handling, allow binary outcomes by @fverac in #816

New Contributors

Full Changelog: v0.14.1...v0.15.0

v0.15.0b1

27 Feb 17:38
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v0.15.0b1 Pre-release
Pre-release

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 #800)
  • Allows missing values in W and sometimes X (by @fverac in #791)
  • Enables federated estimation of linear models (by @kgao in #818)
  • Provides a CATE validation suite for discrete models (by @amarvenu in #777)
  • Enable model selection for first stage models (by @kbattocchi in #808)

New Contributors

Full Changelog: v0.14.1...v0.15.0b1

v0.14.1

22 May 14:21
b0936ac
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What's Changed

Details

Minor updates and bugfixes

  • Avoid returning defaultdict directly when calling est.shap_values @kbattocchi in #709
  • Refactor DynamicDML to remove incompatible method signatures by @kbattocchi in #717
  • Fix bug when using .score in _OrthoLearner subclasses by @kbattocchi in #760

Package changes

Build system changes

Misc

Full Changelog: v0.14.0...v0.14.1

v0.14.0

16 Nov 23:04
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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

Minor updates and bugfixes

Package changes

Build system changes

  • update some pipeline images (macos-12, ubuntu20), fix pycodestyle E275 by @fverac in #672

New Contributors

Full Changelog: v0.13.1...v0.14.0

v0.13.1

16 Nov 19:52
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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

Compatibility changes

Build system improvements

  • Profiling Unit Tests by @xrowan in #575
  • Disable serial tests on macOS by @kbattocchi in #604
  • Adding Microsoft SECURITY.MD by @microsoft-github-policy-service in #622

Full Changelog: v0.13.0...v0.13.1

v0.13.0

09 Feb 19:56
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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

Full Changelog: v0.12.0...v0.13.0

v0.12.0

14 Aug 21:22
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This release contains several major new features:

  • Greatly improved functionality for estimating treatment effects with instrumental variables (#460)
  • A variant of DoubleML for use on dynamic data (#446)
  • A new class for assessing the causal contributions of different features to an outcome, conditional on the other features (this is spread out over a number of PRs)

There have been a few breaking changes:

  • Alpha values for confidence intervals now always default to 0.05; previously some alphas defaulted to 0.1 instead (#482)
  • The deprecated ability to pass X, W, and Z to some fit and score methods by position has been removed (#482)

There have also been many bug fixes in this release; we'd particularly like to highlight:

  • Default values of alpha are now passed correctly through results classes (#476, thanks @mtanghu!)
  • Prevent NaN outputs from GRF in certain corner cases (#480, thanks @arose13!)

v0.12.0b6

07 Aug 18:39
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v0.12.0b6 Pre-release
Pre-release

This is a beta preparing for our next major release, but does not contain any new user-facing features.

v0.12.0b5

07 Aug 18:39
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v0.12.0b5 Pre-release
Pre-release

This is a beta preparing for our next major release, but does not contain any new user-facing features.