决策树算法的研究及实例分析

分类与预测是数据挖掘技术中的一个重要研究领域．而决策树算法又是分类与预测的核心技术算法之一．描述ID3的主要算法，介绍信息增益、系统总熵和信息熵的概念及其计算公式；然后对ID3算法进行了深入地研究与分析；最后把决策树中的ID3算法运用在学生综合测评中．ID3算法最大的缺点是运算复杂，而且要花费较多的时间．

Research into Decision Tree Algorithm and Case Studies

Decision tree algorithm is viewed as one of the core technical algorithms of classification and prediction which is considered a key area in data mining technology. This paper describes the major algorithm of ID3 and introduces such concepts as information gain, total system entropy, and informational entropy, as well as the computational tbrmula. And in-depth research is conducted into ID3 algorithm. Finally, this algorithm of decision tree is used to comprehensively evaluate students＇ performance. ID3 algorithm, however, has its disadvantages, for exmple, complex calculation and time- consuming.