基于模糊聚类的决策树算法在教学质量评价中的应用  

The application study of the decision tree AND fuzzy clustering algorithm on the teaching quality evaluation

作　　者：刘光洁[1] 王文永[2] 吴登峰[1] 黄文博[1] 吴延东[3] 

机构地区：[1]长春师范学院计算机系,吉林长春130032 [2]东北师范大学软件学院,吉林长春130117 [3]吉林省水文水资源局,吉林长春130000

出　　处：《东北师大学报（自然科学版）》2009年第3期36-39,共4页Journal of Northeast Normal University(Natural Science Edition)

基　　金：吉林省重点高新技术项目(20080323)

摘　　要：以目前的高等学校教育为平台,就如何将数据挖掘技术与教学质量评价相结合的问题进行了研究.通过教学质量评价指标体系的有效挖掘,运用模糊聚类的决策树技术来解决目前教学质量评价中的不合理性,提出基于模糊聚类的决策树法的教学质量评价方法,使教学质量评价公平、公正、合理、高效.Curr uation,w research teaching ently, effe results in ctive and scientific methods lack in the field of the school teaching unreasonable phenomenon. The paper attempts to carry on related quality evalanalysis and combining the data mining technique with teaching quality evaluation by mining valid quality evaluation index sign system, making full use of the decision tree technique to solve the unreasonableness of the teaching quality evaluation and putting forward technical method for teaching quality evaluation based on the decision tree and fuzzy clustering algorithm, aimed at making it fair,just,reasonable and efficient.

关 键 词：数据挖掘 决策树 教学质量评价 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] G642.0[自动化与计算机技术—控制科学与工程]