Application of improved decision tree method based on rough set in building smart medical analysis CRM system

被引：3

作者：

Xu H. ^{[1
]}

Wang L. ^{[1
]}

Gan W. ^{[1
]}

机构：

[1] Luoyang Normal University, Henan Luoyang

来源：

International Journal of Smart Home | 2016年 / 10卷 / 01期

关键词：

Attribute reduction; Customer relationship management; Decision tree; Rough set; Smart medical treatment;

D O I：

10.14257/ijsh.2016.10.1.23

中图分类号：

学科分类号：

摘要：

Medical Customer Relationship Management (CRM) is a kind of study method for the patient and potential patient carries on the exchange, timely access to and convey information, tracking to give the necessary guidance. The purpose of community hospital CRM is the daily business management and decision analysis of the hospital with the relationship between doctors and patients. Decision tree learning is an inductive learning algorithm based example. Rough set theory is used to process uncertain and imprecise information. In this paper, a decision tree algorithm based on rough set is proposed, and the improved decision tree algorithm based on rough classification is better than the standard C4.5 algorithm in classification accuracy and regression rate by experiment. Finally, the improved decision tree method is applied to the smart medical analysis CRM system. The experimental results show that the method can improve the management efficiency of CRM. © 2016 SERSC.

引用

页码：251 / 266

页数：15

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