在数据挖掘中，ID3算法对于数据的分类和预测提供了一种重要的途径。该算法以信息论为基础，以信息熵和信息增益度为衡量标准，从而建立决策树，实现对数据的归纳分类。该文对各招生院校的大量数据样本进行分析，依据学校类型、地理位置、校园面积、重点专业和企业口碑这几个较为重要的属性，利用ID3算法，获得不同属性上的信息增益，生成决策树，对学校的等级进行划分。该决策树可为报考学生提供参考，提高报考效率。%In data mining, ID3 algorithm provides an important way for the classification and prediction of the data. The algo-rithm is based on the information theory. It takes the information entropy and information gain degree as the standard to build a decision tree, realizing the classification of data. In this essay, we collect a great quantity of school samples for analysis. According to several important attributes such as the school type, geographic location, the campus area, intensive profession and business rep-utation ,we use ID3 algorithm to get different attributes information gain, and then to generate decision trees.In this way, we can divide the grade of schools. The decision tree can provide a reference for students, improve students' examination efficiency.
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