摘要
心理问题是大学生成长过程中存在的普遍性问题,现代机器学习理论和技术的发展为这一问题的解决提供了支撑。基于此,首先以大学生心理问题分析中常用的数据挖掘技术作为切入点。然后重点讨论了决策技术、随机森林算法和逼近技术、K近邻算法在此领域中的应用,给出了实现方法和步骤。最后通过定量分析法和定性分析法,总结了上述技术算法的结果,希望为大学生心理问题分析工作提供参考。
Psychological problem is a universal problem in the process of college students'growth.The development of modern machine learning theory and technology provides support for the solution of this problem.Based on this,firstly,the data mining technology commonly used in the analysis of College Students'psychological problems is taken as the breakthrough point.Then,the application of decision-making technology,stochastic forest algorithm and approximation technology,K-nearest neighbor algorithm in this field are discussed emphatically,and the implementation methods and steps are given.Finally,through quantitative analysis and qualitative analysis,the results of the above technical algorithms are summarized,hoping to provide a reference for the analysis of College Students'psychological problems.
作者
张海华
Zhang Haihua(Shenzhen University Information Center, Shenzhen Guangdong 518060, China)
出处
《信息与电脑》
2019年第1期24-25,28,共3页
Information & Computer
关键词
心理问题
数据挖掘技术
机器学习
决策技术
逼近技术
psychological problems
data mining technology
machine learning
decision-making technology
approximation technology
