AI RESEARCH
Rule Extraction in Machine Learning: Chat Incremental Pattern Constructor
arXiv CS.LG
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ArXi:2208.00335v3 Announce Type: replace Rule extraction is a central problem in interpretable machine learning because it seeks to convert opaque predictive behavior into human-readable symbolic structure. This paper presents Chat Incremental Pattern Constructor (ChatIPC), a lightweight incremental symbolic learning system that extracts ordered token-transition rules from text, enriches them with definition based expansion, and constructs responses by similarity-guided candidate selection.