摘要
信息论是数据挖掘技术的重要指导理论之一，是决策树算法实现的理论依据．决策树算法是一种逼近离散值目标函数的方法，其实质是在学习的基础上，得到分类规则。本文简要介绍了信息论的基本原理，重点阐述基于信息论的决策树算法，分析了它们目前主要的代表理论以及存在的问题，并用具体的事例来验证。
The information theory is one of the basic theories of Data Mining, and also is the theoretical foundation of the Decision Tree Algorithm. Decision Tree Algorithm is a method to approach the discrete-valued objective function. The essential of the method is to obtain a classification rule on the basis of example-based learning. An example is used to sustain the theory.
出处
《电脑应用技术》
2008年第1期1-7,共7页
Microcomputer Application Technology
关键词
决策树
算法
分类
应用
Decision Tree
Algorithm
Classification
Application
