| 基于Bagging集成学习的字符识别方法 |
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| 引用本文： | 刘余霞,吕虹,胡涛,孙小虎.基于Bagging集成学习的字符识别方法[J].计算机工程与应用,2012,48(33):194-196,211. |
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| 作者姓名： | 刘余霞 吕虹 胡涛 孙小虎 |
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| 作者单位： | 1. 安徽工程大学电气工程学院,安徽芜湖,241000
2. 安徽工程大学电气工程学院,安徽芜湖241000;安徽建筑工业学院电子与信息工程学院,合肥230022 |
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| 基金项目： | 国家自然科学基金（No.61071001）; 安徽省教育厅自然科学基金（No.KJ2008A010） |
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| 摘 要： | 针对字符识别对象的多样性,提出了一种基于Bagging集成的字符识别模型,解决了识别模型对部分字符识别的偏好现象。采用Bagging采样策略形成不同的数据子集,在此基础上用决策树算法训练形成多个基分类器,用多数投票机制对基分类器预测结果集成输出。理论分析与仿真实验结果表明,所提模型相比其他分类方法具有更好的分类能力。
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| 关 键 词： | Bagging 字符识别 集成学习 决策树 Adaboost |
Research on character recognition based on Bagging ensemble learning |
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| LIU Yuxia
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LV Hong
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HU Tao
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SUN Xiaohu.Research on character recognition based on Bagging ensemble learning[J].Computer Engineering and Applications,2012,48(33):194-196,211. |
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| Authors: | LIU Yuxia LV Hong HU Tao SUN Xiaohu |
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| Affiliation: | 1.College of Electrical Engineering,Anhui Polytechnic University,Wuhu,Anhui 241000,China 2.College of Electronic and Information Engineering,Anhui University of Architecture,Hefei 230022,China) |
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| Abstract: | Due to the diversity of character recognition,a character recognition model based on Bagging ensemble is presented,which solves recognition model＇s preferences for certain character.Different datasets are formed by Bagging,and then base-classifier is constructed.Ensemble learning model is built by majority vote.Theoretic analysis and simulation result shows the model owns better classification accuracy than other classification methods. |
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| Keywords: | Bagging character recognition ensemble learning decision tree Adaboost |
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