Causal Scoring: A Framework for Effect Estimation, Effect Ordering, and Effect Classification

Carlos Fernández-Loría, The Hong Kong University of Science and Technology

08.02.2024

12:15 pm - 2:45 pm

LMU Munich, Institute of AI in Management via zoom

The presentation introduces causal scoring for decision-making, with interpretations: effect estimation (EE), effect ordering (EO), and effect classification (EC). EE represents the causal effect, EO as a proxy for magnitude, and EC categorizes individuals. Aligning modeling enhances accuracy. Practical examples demonstrate its utility.

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Causal Scoring: A Framework for Effect Estimation, Effect Ordering, and Effect Classification

Carlos Fernández-Loría, The Hong Kong University of Science and Technology

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