摘要
概述了传统决策树方法的基本原理和优越性,指出了该方法应用于超大数据集的数据挖掘环境时的局限性;着重分五个方面概括了近年来决策树方法在数据挖掘中的主要进展,并讨论了决策树方法面临的挑战及其发展趋势。
This paper summarizes the fundamentals and advantages of traditional decision trees, and the limits of decision trees under data mining environment where magnitude data sets are used. From five aspects, the author then emphasizes the improvements of decision trees in order to meet the requirement of data mining in recent years. Finally, the paper analyses the challenges to the field and the possible improvements of decision tree algorithm in the future.
出处
《计算机应用研究》
CSCD
北大核心
2004年第12期5-8,共4页
Application Research of Computers
关键词
决策树
分类
数据挖掘
Decision Tree
Classification
Data Mining
