The authors describe and prototype a heuristic that extracts hierarchical decision trees from feedforward neural networks by tracing activation paths, without proving equivalence for unseen inputs.
Understanding neural network decisions by creating equivalent symbolic AI models,
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Deriving Equivalent Symbol-Based Decision Models from Feedforward Neural Networks
The authors describe and prototype a heuristic that extracts hierarchical decision trees from feedforward neural networks by tracing activation paths, without proving equivalence for unseen inputs.