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

Source: Towards Data Science

Overview

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. Using the Kaggle Credit Card Fraud dataset (0.17 % fraud rate), the model learned interpretable rules such as:

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