| A Method for Data Classification Based on Discernibility Matrix and Discernibility Function |
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| 作者姓名： | SUN Shi-bao QIN Ke-yun |
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| 作者单位： | [1]School of Science , Southwest Jiaotong University,Chengdu 610031, Sichuan, China [2]Electronic Information Engineering College, Henan University of Science and Technology, Luoyang 471003,Henan, China |
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| 基金项目： | Supported by the National Natural Science Foun dation of China（60474022）. |
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| 摘 要： | 0 IntroductionDiantga .cl Dasesciifsiicoanti otrneies r aengr ie smspioornta,n Bta yperosibalnem claisnsi dfiactaati omnin&-Bayesian network, decision tree1], neural network andSVM2 ,3]are the technologies of data classificationin commonnow. They have extensively appliedin machine learning,ex-pert systemandstatistics etc .Inthese methods ,the most tra-ditional method is C4 .51]based on information entropy,which had extensively applied in practical problems . But themain problemof this me…
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| 关 键 词： | 数据分类 鉴别率矩阵 鉴别率函数 数据挖掘 |
| 文章编号： | 1007-1202（2006）01-0230-04 |
| 收稿时间： | 2005-04-27 |
A method for data classification based on discernibility matrix and discernibility function |
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| SUN Shi-bao QIN Ke-yun.A Method for Data Classification Based on Discernibility Matrix and Discernibility Function[J].Wuhan University Journal of Natural Sciences,2006,11(1):230-233. |
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| Authors: | Sun Shi-bao Qin Ke-yun |
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| Affiliation: | (1) School of Science, Southwest Jiaotong University, 610031 Chengdu Sichuan, China;(2) Electronic Information Engineering College, Henan University of Science and Technology, 471003 Luoyang Henan, China |
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| Abstract: | A method for data classification will influence the efficiency of classification. Attributes reduction based on discernibility matrix and discernibility function in rough sets can use in data classification, so we put forward a method for data classification. Namely, firstly, we use discernibility matrix and discernibility function to delete superfluous attributes in formation system and get a necessary attribute set. Secondly, we delete superfluous attribute values and get decision rules. Finally, we classify data by means of decision rules. The experiments show that data classification using this method is simpler in the structure, and can improve the efficiency of classification. |
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| Keywords: | discernibility matrix discernibility function attributes reduction data classification |
| 本文献已被 CNKI 维普 万方数据 SpringerLink 等数据库收录！ |
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