How a Neural Network Learned Its Own Fraud Rules: A Neuro-Symbolic AI Experiment

Most neuro-symbolic systems inject rules written by humans. But what if a neural network could discover those rules itself?

In this experiment, I extend a hybrid neural network with a differentiable rule-learning module that automatically extracts IF-THEN fraud rules during training. On the Kaggle Credit Card Fraud dataset (0.17% fraud rate), the model learned interpretable rules such as:

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