江汉大学学报(自然科学版) ›› 2015, Vol. 43 ›› Issue (4): 371-375.

• 计算机与信息科学 • 上一篇    下一篇

决策树算法的研究及其在大学生心理健康数据处理中的应用

晏 杰   

  1. 武夷学院 数学与计算机学院, 福建 武夷山 354300
  • 出版日期:2015-08-28 发布日期:2015-08-13
  • 作者简介:晏杰( 1977—), 男 , 讲师 , 硕士, 研究方向: 计算机应用 、 算法与数据结构及数据挖掘。
  • 基金资助:
    福建省“大学生创新训练计划 ”项目( 201310397022); 武夷学院校科研基金资助项目( XL201307)

Research on Decision Tree and Its Application on Students′ Mental Health Data Treatment

YAN Jie   

  1. College of Mathematics and Computer Science, Wuyi University, Wuyishan 354300, Fujian, China
  • Online:2015-08-28 Published:2015-08-13

摘要: 决策树分类是数据挖掘中的一种重要方法。 探讨了决策树算法的基本思想和常用算法, 并将决策树挖掘技术应用于大学生心理健康数据, 分析挖掘影响大学生心理健康的因素。 文章选择 C5.0 算法, 通过 Clemen?tine12.0 进行决策树挖掘模型的构建, 建立数据流, 通过不断测试分析, 发现影响大学生心理健康主要症状是强迫症。 以强迫症为分类目标查看模型, 可以了解到焦虑症和人际关系也起到很大的影响作用 。 将目标属性分别设置为焦虑_程度和人际关系 _程度, 输出变量设为剩余的 9 个因子变量, 执行数据流挖掘出导致强迫症的主要原因 , 为指导心理健康的工作人员提供参考。

关键词: 数据挖掘, 决策树, 心理健康, 大学生

Abstract: Classification of decision tree is an important method in data mining. The basic ideas and common algorithms of decision tree algorithm are discussed, the decision tree mining is applied to students′ mental health data analysis, and to analyse the impacting factors on students′ mental health.With the C5.0 algorithm, performed by Clementine 12.0, the decision tree mining model was constructed, the data flow was also set, with continuous test and analysis, discovered that compulsion was the main symptom which impacted the mental health of students. To view the model with compulsion as the classification object, it can be find out that anxiety and social relationship also have big influences. The target attribute were set as anxiety_degree and social relationship_degree, output variables were set as the left nine factors, dug out the main factors which cause the compulsion, to provide the reference to the mental health domain.

Key words: data mining, decision tree, mental health, student

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