数据挖掘分类算法研究综述  

Review of Classification Algorithms in Data Mining

作　　者：王刚[1] 黄丽华[1] 张成洪[1] 夏洁[2] 

机构地区：[1]复旦大学管理学院,上海200433 [2]中南大学信息工程学院,长沙410083

出　　处：《科技导报》2006年第12期73-76,共4页Science & Technology Review

基　　金：国家自然科学基金项目(70571016;70471011)

摘　　要：随着数据库应用的不断深化,数据库的规模急剧膨胀,数据挖掘已成为当今研究的热点;特别是其中的分类问题,由于其使用的广泛性,现已引起了越来越多的关注。对数据挖掘分类问题的研究现状进行了综述:首先对研究比较多的基于判定树的归纳分类、基于人工神经网络的分类和基于统计的贝叶斯分类作了详细的讨论;然后对目前新提出的几种算法作了简要分析;最后根据数据挖掘的发展现状和研究重点对数据挖掘分类算法的发展趋势作了展望。With the application of database deepening and the size of database expanding quickly, Data Mining has recently become the hotspot. Classification, the problem among them especially because of its extensive usage, has acquired more and more concerns presently. On account of this, the article carried on an overview according to the present condition of data mining＇s classification. Firstly, the article discussed in detail the classification methods that were researched widely, such as Decision Tree, Artificial Neural Network and Bayesian classification. Secondly, the article analyzed the new brought forward algorithms briefly, lastly, according to the data mining＇s developmental conditions and the emphases of research, the article forecasted the trends of the next research of classification.

关 键 词：数据挖掘 分类 算法 综述 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]