摘要
决策树算法是数据挖掘领域的一个研究热点,通常用于提取描述重要数据类的模型或预测未来的数据趋势。该文介绍了决策树及其发展过程,重点阐述了三种典型的决策树算法,分析了它们的优缺点,并对三种算法进行了比较,最后探讨了决策树算法的改进方向。
Decision tree algorithm is a research hotspot in the field of data mining. It is usually used to extract models that describe important data classes or predict future data trends. The paper introduces the decision tree and its development process. Three typical decision tree algorithms are emphatically described, their advantages and disadvantages are analyzed, and the three algorithms are compared. Finally, the improvement direction of the decision tree algorithm is discussed.
出处
《电脑知识与技术》
2018年第3Z期175-177,共3页
Computer Knowledge and Technology
关键词
数据挖掘
决策树
分类
data mining
decision tree
classification
