基于C4.5算法的大学阳光体育系统设计与实现

Sunlight Sports System Design and Implementation Based on Decision Tree

随着中国大学生规模的不断扩大,大学生的数量迅速增加,因此与学生相关的人体测量数据也显著增加,包括学生出勤信息和身体健康测试数据,因此做好数据管理工作是当前高校体育教育发展的必然要求。随着计算机技术的快速发展,数据挖掘技术已被应用于许多领域。本文从阳光体育开始,利用数据挖掘的C4.5算法构建基于学生真实体质健康测试数据的决策树,生成规则和知识。通过对决策树的分析,可以了解影响学生身体健康的重要因素与指标之间的关系,以指导高校适时调整体育教育的管理手段,从而全面提高学生的身体素质。

With the continuous expansion of the scale of Chinese college students, the number of college students has rapidly increased, so the number of anthropometric data related to students increase significantly, including student attendance information and physical health test data. Therefore, a good job in data management is an inevitable requirement for the development of physical education in colleges and universities. With the rapid development of computer technology, data mining technology is applies in many fields. This article starts from Sunshine Sports, uses the C4.5 algorithm of data mining to build a decision tree based on the student’s real physique health test data, and generates rules and knowledge. Through the analysis of the decision tree, the relationship between important factors and indicators is abtained that affect students’ physical health, in order to guide decision-makers timely adjustment of management tools, so as to comprehensively improve the students’ physical fitness.