ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
This is a major update of the library, with several important improvements, as well as a number of bug-fixes and minor improvements.
Full Changelog: https://github.com/py-why/EconML/compare/v0.14.1...v0.15.0
This beta has many bug fixes and provides several big improvements:
Full Changelog: https://github.com/py-why/EconML/compare/v0.14.1...v0.15.0b1
est.shap_values @kbattocchi in https://github.com/py-why/EconML/pull/709
DynamicDML to remove incompatible method signatures by @kbattocchi in https://github.com/py-why/EconML/pull/717
score in _OrthoLearner subclasses by @kbattocchi in https://github.com/py-why/EconML/issues/760
Full Changelog: https://github.com/py-why/EconML/compare/v0.14.0...v0.14.1
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.
Full Changelog: https://github.com/microsoft/EconML/compare/v0.13.1...v0.14.0
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.
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.
Full Changelog: https://github.com/microsoft/EconML/compare/v0.12.0...v0.13.0
This release contains several major new features:
There have been a few breaking changes:
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:
This is a beta preparing for our next major release, but does not contain any new user-facing features.
This is a beta preparing for our next major release, but does not contain any new user-facing features.
This is a beta preparing for our next major release, but does not contain any new user-facing features.