Comment: Causal Inference Competitions: Where Should We Aim?
2019
Data competitions proved to be highly beneficial to the field of
machine learning, and thus expected to provide similar advantages in the field
of causal inference. As participants in the 2016 and 2017 Atlantic Causal Inference
Conference (ACIC) data competitions and co-organizers of the 2018
competition, we discuss the strengths of simulation-based competitions and
suggest potential extensions to address their limitations. These suggested
augmentations aim at making the data generating processes more realistic
and gradually increase in complexity, allowing thorough investigations of algorithms’
performance. We further outline a community-wide competition
framework to evaluate an end-to-end causal inference pipeline, beginning
with a causal question and a database, and ending with causal estimates.
- Correction
- Source
- Cite
- Save
- Machine Reading By IdeaReader
9
References
1
Citations
NaN
KQI