Modeling and Discovering Direct Causes for Predictive Models

• URL: http://arxiv.org/abs/2412.02878v2
• Date: Sat, 17 May 2025 03:06:10 GMT
• Title: Modeling and Discovering Direct Causes for Predictive Models
• Authors: Yizuo Chen, Amit Bhatia,
• Abstract summary: We introduce a causal modeling framework that captures the input-output behavior of predictive models.<n>We then present sound and complete algorithms for discovering direct causes (from data) under some assumptions.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We introduce a causal modeling framework that captures the input-output behavior of predictive models (e.g., machine learning models). The framework enables us to identify features that directly cause the predictions, which has broad implications for data collection and model evaluation. We then present sound and complete algorithms for discovering direct causes (from data) under some assumptions. Furthermore, we propose a novel independence rule that can be integrated with the algorithms to accelerate the discovery process, as we demonstrate both theoretically and empirically.

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