Double Machine Learning and Automated Confounder Selection

Paul Hünermund

Double Machine Learning and Automated Confounder Selection

Department of Strategy and Innovation

Research output: Non-textual form › Sound/Visual production (digital) › Communication

Abstract

Double machine learning (DML) is becoming an increasingly popular tool for automatic model selection in high-dimensional settings. Paul Hünermund discusses that DML is very sensitive to the inclusion of even a few “bad controls” in the covariate space.

Original language	English
Publication date	20 Apr 2022
Place of Publication	London
Media of output	Video
Size	05:54
Publication status	Published - 20 Apr 2022

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https://faculti.net/double-machine-learning-and-automated-confounder-selection/Licence: Unspecified

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