| 基于对应分析的支持向量机分类研究 |
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| 引用本文： | 王娟,贺兴时,赵飞军.基于对应分析的支持向量机分类研究[J].四川理工学院学报(自然科学版),2010,23(5). |
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| 作者姓名： | 王娟 贺兴时 赵飞军 |
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| 基金项目： | 陕西省教育厅自然科学专项基金 |
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| 摘 要： | 提出了基于对应分析的支持向量机分类模型。该模型通过对应分析可以同时对变量及样本进行降维和消除相关性,从而在降低SVM训练时间的基础上有效地提高了SVM的分类精度。实验结果表明该方法是可行的。
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| 关 键 词： | 支持向量机 对应分析 分类模型 因子分析 |
Research of SVM's Classification Based on Correspondence Analysis |
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| WANG Juan,HE Xing-shi,ZHAO Fei-jun.Research of SVM's Classification Based on Correspondence Analysis[J].Journal of Sichuan University of Science & Engineering:Natural Science Editton,2010,23(5). |
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| Authors: | WANG Juan HE Xing-shi ZHAO Fei-jun |
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| Abstract: | A model of SVM's classification based on correspondence analysis is proposed.This model not only can reduce the dimension of variables and samples,but eliminate the correlation between them.Thereby,the classification accuracy of SVM can be effectively improved by reducing the training time of SVM.Experimental results show that the method is feasible. |
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| Keywords: | Support Vector Machine(SVM) correspondence analysis classification model factor analysis |
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