AN INTELLIGENT NEURAL NETWORK RULE EXTRACTION TECHNIQUE

摘要：

Most of decision making studies focus primarily on developing classification models with high perspective accuracy without any attention to explaining how the classifications being made. We deals with the neural network rule extraction techniques based on the Genetic Programming (GP) to build intelligent and explanatory evaluation systems. GP is utilized to automatize the rule extraction process in the trained neural networks where the decision basically boils down to a binary classification problems. Simple and relevant classification rules are obtained by pruning weight among neurons to obtain simple but substantial binary expressions.

关键词： Neural Network Rule Extraction Genetic Programming Classification Rules

作者: Yunling Liu Jianjun Lu

作者单位: College of Information and Electrical Engineering, China Agricultural University Beijing, 100083, Ch Graduate School of Economics, Kyushu University Fukuoka, 812-8581, Japan

会议类型: 国际会议

会议名称: 2006 International Symposium on Distributed Computing and Applications to Business,Engineering and Science(2006年国际电子、工程及科学领域的分布式计算应用学术研讨会)

会议地点: 杭州

会议语种:英文

页码: 681-684

在线出版日期: 2006-10-12（万方平台首次上网日期，不代表论文的发表时间）