Score Domain Adaptation Forest

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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Score Domain Adaptation Forest #523

Open jbel1026 opened 2 years ago

jbel1026 commented 2 years ago

The econml.metalearners.DomainAdaptationLearner does not have a score attribute. Is there a way to score it similar to CausalforestDML and DRL?

est.score()

jbel1026 commented 2 years ago

Also to add to this, is there functionality to .tune() the domain adaptation forest and the doubly robust forest in a similar way that you can for DML?

Thanks!