出版社：University of Malaya * Faculty of Computer Science and Information Technology
摘要：In machine learning, a key aspect is the acquisition of knowledge. As problems become more complex, and experts become scarce, the manual extraction of knowledge becomes very difficult. Hence, it is important that the task of knowledge acquisition be automated. This paper proposes a novel method that integrates neural network and expert system paradigms to produce an automated knowledge acquisition system. A rulegeneration algorithm is proposed, whereby symbolic rules are generated from a neural network that has been trained by an unsupervised Kohonen selforganising map (KSOM) learning algorithm. The generated rules are evaluated and verified using an expert system inference engine. To demonstrate the applicability of the proposed method to realworld problems, a case study in medical diagnosis is presented.
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