分类是数据挖掘的重要组成部分,分类可用于提取描述重要数据类的模型或预测未来的数据趋势,在众多的分类算法中决策树方法在可理解度和易使用等方面优于其他的分类方法。本文以高职院校学生信息与专业选择之间的关系分析为例,完整地给出了决策树分类ID3算法的理论基础和实践的全过程,实验结果表明了决策树分类ID3算法在学生信息分析中的有效性。 Classification is an important part of data mining. Classification can be used to extract models that describe important data classes or to predict future data trends. Among many classification algorithms, decision tree methods are superior to other classification methods in terms of comprehensibility and ease of use . In this paper, the relationship between vocational college students’ information and professional choice is taken as an example to show the whole process of theoretical and practical decision tree classification ID3 algorithm. The experimental results show that the decision tree classification ID3 algorithm, The validity of the analysis.