From Log-Odds to Shapley Values: An Explanatory Geometry for the Weighted Naive Bayes Classifier

arXiv:2610.10642 · stat.ML, cs.AI, cs.LG · Submitted 2026-10-07 · Read on arXiv

stat.ML, cs.AI, cs.LG

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Shapley values — 23× in this paper · explained in 2 episodes
• AUC — 6× in this paper · explained in 2 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Clustering — 2× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Area Under the Curve (AUC) — 1× in this paper · explained in 1 episode
• Conformal Prediction — 1× in this paper · explained in 5 episodes
• Explainability — 1× in this paper · explained in 3 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes

Sources

• Khiops: An End-to-End, Frugal AutoML and XAI Machine Learning Solution for Large, Multi-Table Databases
• Fractional Naive Bayes (FNB): non-convex optimization for a parsimonious weighted selective naive Bayes classifier

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