The refinement of probabilistic rule sets: Sociopathic interactions

摘要

Probabilistic rules in a classification expert system can result in a sociopathic knowledge base, as a consequence of the assumption of conditional independence between observations and rule modularity. A sociopathic knowledge base has the property that all the rules are individually judged to be correct rules, yet a subset of the knowledge base gives better classification accuracy than the original knowledge base, independent of the amount of computational resources that are available.