Computer Science ›› 2013, Vol. 40 ›› Issue (Z11): 98-100.

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Multi-label Text Classification Algorithm Based on Hyper Ellipsoidal SVM

QIN Yu-ping,WANG Yi,LUN Shu-xian and WANG Xiu-kun   

  • Online:2018-11-16 Published:2018-11-16

Abstract: A new multi-label text classification algorithm based on hyper ellipsoidal support vector machines was proposed. To each class sample,the hyper ellipsoidal that includes as much the class samples as possible and push the outlier samples away is trained in the featuer space. For the sample to be classified,the mahalanobis distance from the sample mapping to the center of each hyper ellipsoidal were used to decide the sample classs. The results of the experiment show that the proposed algorithm has a higher classification accuracy.

Key words: Hyper ellipsoidal SVM,Multi-label classification,Mahalanobis distance

[1] Vapnik V.The Nature of Statistical Learning Theory[M].New York:Springer,1995
[2] Joachims T.Text Categorization with Support Vector Ma-chines:Learning with Many Relevant Feature[A]∥Procee-dings of ECML-98,10th European Conference on Machine Learning[C].Berlin:Springer,1998:137-142
[3] 孙晋文,肖建国.基于SVM的中文文本分类反馈学习技术的研究[J].控制与决策,2004,9(8):927-930
[4] Bennett K P.Combining Support Vector and Mathematical Programming Methods for Classification[A]∥Advances in Kernel Methods:Support Vector Learning[C].Cambridge,MA:MIT press,1999:307-326
[5] Krebel U G.Pairwise Classification and Support Vector Ma-chines[A]∥Advances in Kernel Methods:Support Vector Learning[C].Cambridge,MA:MIT press,1999:255-268
[6] Platt J C,Cristianini N,Shawe-Taylor J.Large Margin DAGs for multiclass classification[A]∥Advances in Neural Information Processing Systems[C].Cambridge,MA:MIT Press,2000:547-553
[7] 王晔,黄上滕.基于支持向量机的文本兼类标注[J].计算机工程与应用,2006,2(2):182-185
[8] 秦玉平,王秀坤,王春立.基于超球支持向量机的兼类文本分类算法研究[J].计算机工程与应用,2008,4(19):166-168
[9] 秦玉平,陈一荻,王春立,等.一种新的兼类文本分类方法[J].计算机科学,2011,38(11):204-205
[10] Wei X K,Huang G B.Mahalanobis Eillpsoidal Learning Machine for One Class Classification[C]∥International Conference on Machine Learning and Cybernetics.2007:3528-3533
[11] 李永新,薛贞霞.最大间隔椭球形多类分类算法[J].计算机工程,2010,6(7):185-189
[12] 李建民,李永新,薛贞霞.基于马氏椭球学习机的监督野点探测[J].计算机工程与应用,2009,5(13):200-210

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