| 混合式朴素贝叶斯分类模型 |
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| 引用本文： | 董立岩,刘光远,苑森淼,李永丽,孙铭会. 混合式朴素贝叶斯分类模型[J]. 吉林大学学报(信息科学版), 2007, 25(1): 57-61 |
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| 作者姓名： | 董立岩 刘光远 苑森淼 李永丽 孙铭会 |
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| 作者单位： | 吉林大学,计算机科学与技术学院,长春,130012;吉林大学,通信工程学院,长春,130022;东北师范大学,计算机学院,长春,130024 |
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| 摘 要： | 为了降低朴素贝叶斯分类模型的独立性假设约束,提出一种混合式朴素贝叶斯分类模型(MBN:Mixed Naive Bayes)。通过分析贝叶斯定理,把条件属性集合划分成若干个独立的属性子集,用树增广朴素贝叶斯分类对属性子集分别进行分类学习,通过公式进行整合。将该模型算法与朴素贝叶斯及树增广朴素贝叶斯进行实验比较,实验结果表明MBN分类器在多数数据集上具有较高的分类正确率。
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| 关 键 词： | 贝叶斯定理 朴素贝叶斯 数据挖掘 分类 |
| 文章编号： | 1671-5896(2007)01-0057-05 |
| 修稿时间： | 2006-03-06 |
Mixed Naive Bayes Classifier Model |
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| DONG Li-yan,LIU Guang-yuan,YUAN Sen-miao,LI Yong-li,SUN Ming-hui. Mixed Naive Bayes Classifier Model[J]. Journal of Jilin University:Information Sci Ed, 2007, 25(1): 57-61 |
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| Authors: | DONG Li-yan LIU Guang-yuan YUAN Sen-miao LI Yong-li SUN Ming-hui |
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| Abstract: | In order to decrease the attribute independence assumption which is made by Naive Bayesian,a new Bayesian model MBN(Mixed Naive Bayes) is introduced.It divides attribute sets into several independent subsets by analyzing Bayesian theorem. The subsets are trained by TAN(Tree Augmented Naive Bayes) and the results are integrated by formula.MBN classifier is compared with Naive Bayes classifier and TAN classifier by an experiment.Experimental results show that this model has higher classification accuracy in most data sets. |
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| Keywords: | bays theorem naive bayes data mining classify |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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