| 基于Bayes的有噪训练集去噪方法研究 |
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| 引用本文： | 罗俊杰,孙江文,王崇骏,陈世福.基于Bayes的有噪训练集去噪方法研究[J].计算机科学,2008,35(9):213-216. |
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| 作者姓名： | 罗俊杰 孙江文 王崇骏 陈世福 |
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| 作者单位： | 南京大学计算机软件新技术国家重点实验室,计算机科学与技术系,南京,210093 |
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| 基金项目： | 国家自然科学基金，江苏省自然科学基金，江苏省高技术研究发展计划 |
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| 摘 要： | 利用有噪训练集训练分类器的过程中,去噪是基本的预处理步骤.传统的去噪工作只是简单地删除被标记为噪声的实例.显然,这样处理会清除噪声实例中的有用信息.本文提出一种基于Bayes的去噪方法,不但能辨识出噪声而且能纠正噪声实例的错误类标,从而保证其有效信息不会丢失.
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| 关 键 词： | 噪声 噪声辨别 噪声纠正 |
Identifying and Correcting Mislabled Training Instances Using Bayes |
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| LUO Jun-jie,SUN Jiang-wen,WANG Chong-jun,CHEN Shi-fu.Identifying and Correcting Mislabled Training Instances Using Bayes[J].Computer Science,2008,35(9):213-216. |
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| Authors: | LUO Jun-jie SUN Jiang-wen WANG Chong-jun CHEN Shi-fu |
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| Affiliation: | LUO Jun-jie SUN Jiang-wen WANG Chong-jun CHEN Shi-fu(National Key Laboratory for Novel Software Technology,Department of Computer Science , Technology,Nanjing University,Nanjing 210093,China) |
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| Abstract: | De-noising is a basic pretreatment in the process of training a classifier.Most traditional de-noising approaches only delete instances tagged as noise which obviously also eliminates the useful information in these instances.A new approach is presented with which we can not only identify noise but also correct it,so that the useful information will be reserved. |
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| Keywords: | Noise Noise identifying Noise correcting |
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