摘要
机器学习与数据挖掘是研究从数据中提取知识的理论和技术,目前这些理论与技术在世界主要经济领域中日益得到广泛应用。分类模型是机器学习和数据挖掘最重要的研究内容之一。在众多的分类方法中,贝叶斯分类器在计算上具有非常高的效率,在某些应用问题上表现出诱人的分类精度,因而广泛地应用于许多实际领城中。为进一步对这一领域展开研究,介绍了贝叶斯分类器的原理、当前现状及下一步的研究重点。
Machine learning and data mining is the theory and technology that discover knowledge from database. Recently, the theory and technology have been widely applied in main world economic filed. Classification model is one of the key searching content in machine learning and data mining. In all the classification methods, Bayesian classifiers have high effect and the accuracy is satisfactory, so it has many application in actuality. The paper introduces the theory, situation and emphasis of Bayesian classifters for further research.
出处
《长春理工大学学报（自然科学版）》
2006年第3期51-53,共3页
Journal of Changchun University of Science and Technology(Natural Science Edition)
关键词
数据挖掘
分类模型
贝叶斯分类器
data mining
classification model
Bayesian classifiers
