Scaling the Explanation of Multi-Class Bayesian Network Classifiers

Yaofang Zhang; Adnan Darwiche

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arXiv · 2603.14594

Scaling the Explanation of Multi-Class Bayesian Network Classifiers

Yaofang Zhang·Adnan Darwiche

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Abstract

We propose a new algorithm for compiling Bayesian network classifier (BNC) into class formulas. Class formulas are logical formulas that represent a classifier's input-output behavior, and are crucial in the recent line of work that uses logical reasoning to explain the decisions made by classifiers. Compared to prior work on compiling class formulas of BNCs, our proposed algorithm is not restricted to binary classifiers, shows significant improvement in compilation time, and outputs class formulas as negation normal form (NNF) circuits that are OR-decomposable, which is an important property when computing explanations of classifiers.

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Yaofang Zhang, Adnan Darwiche. 2026-03-15. Scaling the Explanation of Multi-Class Bayesian Network Classifiers. https://arxiv.org/abs/2603.14594

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