Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 428-431.doi: 10.11896/j.issn.1002-137X.2017.11A.091

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Weighted Least Squares Support Vector Machine Based on Entropy Evaluation

LIU Chang and FAN Bin   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Support vector machine is a kind of machine learning algorithm based on statistical learning theory,which has a desirable modeling performance for nonlinear and high-dimensional data,even in the case of small samples.Typically,the data with multiple features would be normalized due to different dimensions.However,it ignores the dissimilarity of different features.A weighted least squares support vector machine was proposed.According to the entropy evaluation method,the feature weights may be determined so that the data could be normalized and weighted.Then the system model would be established through the least squares support vector machine.The experimental results demonstrate the effectiveness and superiority of the proposed method for the system with multiple features.

Key words: Support vector machine,Entropy evaluation method,Multiple features,Feature weight

[1] HAYKIN S.Neural Networks:A Comprehensive Foundation[M].Macmillan,1998:71-80.
[2] 焦李成.神经网络系统理论[M].西安电子科技大学出版社,1990.
[3] 张木想,马缚龙,肖国镇.神经网络优化计算的新方法[J].电子学报,1993(7):1-7.
[4] UKIL A.Support Vector Machine[J].Computer Science,2002,1(4):1-28.
[5] SUYKENS J A K,GESTEL T V,BRABANTER J D,et al.Least Square Support Vector Machine[J].Euphytica,2002,2(2):1599-1604.
[6] 阎威武,邵惠鹤.支持向量机和最小二乘支持向量机的比较及应用研究[J].控制与决策,2003,18(3):358-360.
[7] 李盼池,许少华.支持向量机在模式识别中的核函数特性分析[J].计算机工程与设计,2005,26(2):302-304.
[8] 巩知乐,张德贤,胡明明.一种改进的支持向量机的文本分类算法[J].计算机仿真,2009,26(7):164-167.
[9] 何江平,文俊浩,邓恬洁,等.基于支持向量机的图像识别[J].重庆大学学报(自然科学版),2006,29(1):57-60.
[10] 叶美盈,汪晓东,张浩然.基于在线最小二乘支持向量机回归的混沌时间序列预测[J].物理学报,2005,54(6):2568-2573.
[11] 柳小桐.BP神经网络输入层数据归一化研究[J].机械工程与自动化,2010(3):122-123.
[12] 刘冲,赵海滨,李春胜,等.基于频带能量归一化和SVM-RFE的ECoG分类[J].仪器仪表学报,2011,32(3):534-539.
[13] 常军,李祯,朱业玉,等.基于支持向量机(SVM)方法的冬季温度预测[J].气象科技,2005(s1):102-106.
[14] 黄安民,焦淑菲,任海青,等.支持向量机结合近红外光谱法测定杉木木质素的含量[J].林产化学与工业,2009,29(5):1-5.
[15] 郭显光.熵值法及其在综合评价中的应用[J].财贸研究,1994(6):56-60.
[16] PENG X,XU D.Twin Mahalanobis distance-based support vector machines for pattern recognition[J].Information Sciences,2012,200(1):22-37.

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