08
Feb
![Teaser image to Causal Scoring: A Framework for Effect Estimation, Effect Ordering, and Effect Classification](/images/logos/som-ki-keynotes.jpg)
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AI Keynote Series
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 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.