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题名: Text classification model of Uyghur based on improved Bayes
作者: Zhou, Xi
通讯作者: Zhou, X.
刊名: Journal of Computational Information Systems
发表日期: 2013
卷: 9, 期:11, 页:4319-4327
收录类别: EI
摘要: Nai¨ve Bayesian is a simple and efficient pattern recognition algorithm, and has been widely used in text classification. But the assumption of Nai¨ve Bayesian is often not hold in the real application. To improve the performance of the Classifier, a weighted Bayesian method is proposed based on feature selection weight for taking into account different conditions have different effects to the decision conditions. Firstly, represent the effect value of every feature by the combination of the Chi Square value and IDF (Inverse Document Frequency). Then, the weight of every feature is computed by the effect value. Lastly, weighted Bayesian Classifier is built on the weight. By experiments, This method has a better classification performance than Nai¨ve Bayesian Classifier.
内容类型: 期刊论文
URI标识: http://ir.xjipc.cas.cn/handle/365002/4117
Appears in Collections:多语种信息技术研究室_期刊论文

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作者单位: The Xinjiang Technical Institute of Physics and Chemistry, Urumqi 830011, China;Graduate University of Chinese Academy of Sciences, Beijing 100190, China

Recommended Citation:
Zhou, Xi. Text classification model of Uyghur based on improved Bayes[J]. Journal of Computational Information Systems,2013,9(11):4319-4327.
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