数据挖掘分类技术研究与分析  

Research on Classification Technology in Data Mining

作　　者：李秀娟[1] 田川[2,3] 冯欣[1] 

机构地区：[1]西安财经学院信息学院,陕西西安710100 [2]西北工业大学电子信息学院,陕西西安710072 [3]空军驻西北地区军事代表室,陕西西安710043

出　　处：《现代电子技术》2010年第20期86-88,共3页Modern Electronics Technique

摘　　要：分类技术是数据挖掘中的核心和基础技术,在此就数据挖掘分类技术的主要算法进行了对比分析研究。对目前研究比较多的基于决策树、贝叶斯和人工神经网络的分类方法做了详细的讨论,对其他新提出的几种算法做了简要分析,论述了每种分类算法的优缺点,并给出了相应的应用领域,最后对分类技术的研究重点和发展趋势做了展望。The classification technology has a wide range of applications, and is the core and foundation of data mining. The comparative analysis is carried out for the primary algorithm of the classification technology in data mining. The classification technologies that have been researched widely such as decision tree, Bayesian classification and artificial neural network are discussed in detail. The new brought forward algorithms are analyzed briefly. The advantages and disadvantages of each classification algorithm are elaborated. The research trend of the classification technology is forecasted.

关 键 词：数据挖掘 决策树 贝叶斯分类 人工神经网络 

分 类 号：TN911-34[电子电信—通信与信息系统] TP311[电子电信—信息与通信工程]