Production System Development for Expert Systems Using a Recursive Partitioning Induction Approach: An Application to Mortgage, Commercial, and Consumer Lending
提出一种递归划分分析方法用于专家系统的知识获取，在抵押、商业和消费贷款数据集上测试，相比传统归纳算法和统计模型，该方法用更少变量取得更优分类效果。
ABSTRACT The concepts of expert systems and decision support systems have received considerable attention recently. While systems have been proposed for various problem areas in business, difficulties still exist in the knowledge acquisition phase of development. This paper presents a recursive partitioning analysis (RPA) approach to knowledge acquisition. The RPA production system approach was applied to data sets representing the mortgage, commercial, and consumer lending problems. Comparison of the classification rates across these problems to the results of a generalized inductive inference production system (Quinlan's ID3 algorithm) and across the mortgage and commercial lending problems to traditional statistical modeling approaches indicated that the RPA approach provided superior results while using fewer variables.