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py-why / EconML

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.
https://www.microsoft.com/en-us/research/project/alice/
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Improve model selection #848

Closed kbattocchi closed 7 months ago

kbattocchi commented 8 months ago

Fixes two-stage model selection used by IV models, so that we first select and train nuisances for y, t, etc., and then select and train the covariance model. Added central documentation for how to specify how to select models and simplifies the documentation for each estimator by pointing there.

fverac commented 7 months ago

Should we add a test that sklearn pipelines work correctly?

kbattocchi commented 7 months ago

Should we add a test that sklearn pipelines work correctly?

Good point, I'll add several tests covering this functionality.