| 一种基于RS和SVM的目标对象的性能分类方法 |
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| 引用本文： | 彭建,刘金平,柳林.一种基于RS和SVM的目标对象的性能分类方法[J].长沙理工大学学报(自然科学版),2005,2(2):63-66. |
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| 作者姓名： | 彭建 刘金平 柳林 |
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| 作者单位： | 长沙理工大学,计算机与通信工程学院,湖南,长沙,410076;长沙理工大学,计算机与通信工程学院,湖南,长沙,410076;长沙理工大学,计算机与通信工程学院,湖南,长沙,410076 |
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| 摘 要： | 提出了一种基于粗糙集(RS)和支持向量机(SVM)的目标对象的性能分类方法，该方法将RS和SVM结合在一起对性能进行分类．在分类之前，首先利用RS对属性进行约简，将约简后的属性作为输入端输入到SVM中进行训练，再用训练好的SVM对测试集进行测试．测试结果表明，该方法分类的精度比较高，速度比较快．
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| 关 键 词： | 粗糙集 支持向量机 属性约简 性能分类 |
| 文章编号： | 1672-9331(2005)02-0063-04 |
| 修稿时间： | 2005年2月23日 |
Object's Performance Classification Based on RS and SVM |
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| PENG Jian,LIU Jin-ping,LIU Lin.Object's Performance Classification Based on RS and SVM[J].Journal of Changsha University of Science and Technology:Natural Science,2005,2(2):63-66. |
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| Authors: | PENG Jian LIU Jin-ping LIU Lin |
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| Abstract: | A method of object's performance classification based on Rough Set(RS) and Support Vector Machines(SVM) was proposed and it classifies the object's performance by composing the RS and SVM.Before classification we use the RS to reduce the attributes of the object,then train the SVM by sending the reduced attributes as the input and finally verify the test data with the trained SVM.The test results show that the accuracy of the method is quite high,and the speed is very fast. |
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| Keywords: | rough set attribute reduction performance classification |
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