AINeutralarXiv – CS AI · 14h ago6/10
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The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction
A comprehensive study of Markov boundaries in tabular prediction reveals that while oracle boundaries significantly improve model performance, practical causal discovery methods fail to recover them cost-effectively. The research identifies fundamental misalignments between structural recovery optimization and predictive performance, suggesting that prediction-focused feature selection requires different approaches than theoretical assumptions propose.