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电子学报  2012 

多目标优化算法在多分类中的应用研究

DOI: 10.3969/j.issn.0372-2112.2012.11.019, PP. 2264-2269

Keywords: 多分类,多目标优化,聚类,MOPSO,NSGA-II

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Abstract:

Cai等人用多目标粒子群算法(MOPSO)优化多目标聚类学习和分类学习框架(MSCC)的多目标问题时,种群只能得到少量的非支配解,不利于种群优化.而在此情况下,NSGA-II由于采用了Pareto排序的方法,种群中会保留大量优秀的支配解,有利于种群优化,所以本文引进了NSGA-II优化MSCC框架的多目标问题.通过对数据集的测试,验证了在NSGA-II的优化下,对于大多数测试问题,MSCC框架设计的分类器的最大分类正确率高于MOPSO优化MSCC框架的结果.进而对实验结果做了进一步分析,发现了最大正确率不随多目标优化算法的优化过程而提高的问题.

References

[1]  R Tagliaferri,A Staiano,D Scala.A supervised fuzzy clustering for radial basis function neural networks training .Joint 9th IFSA World Congress and 20th NAFIPS International Conference .USA:IEEE Press,2001.3:1804-1809.
[2]  Y J Oyang,S C Hwang,Y Y Ou,C Y Chen,Z W Chen.Data classification with radial basis function networks based on a novel kernel density estimation algorithm[J].IEEE Transactions on Neural Networks,2005,16(1):225-236.
[3]  I Maglogiannis,H Sarimveis,C T Kiranoudis.A Chatziioannou,N Oikonomou,V Aidinis.Radial basis function neural networks classification for the recognition of idiopathic pulmonary fibrosis in microoscopic images[J].IEEE Transactions on Information Technology in Biomedicine,2008,12(1):42-54.
[4]  米爱中,郝红卫,郑雪峰,涂序彦.一种自整定权值的多分类器融合方法[J].电子学报,2009,37(11):2604-2609. MI Ai-zhong,HAO Hong-wei,ZHENG Xue-feng,TU Xu-yan.A method of multiple classifier fusion with self-adjusting weights[J].Acta Electronica Sinica,2009,37(11):2604-2609.(in Chinese)
[5]  连可,黄建国,王厚军,龙兵.一种基于遗传算法的SVM决策树多分类策略研究[J].电子学报,2008,36(8):1502-1507. LIAN Ke,HUANG Jian-guo,WANG Hou-jun,LONG Bing.Study on a GA-based SVM decision-tree multi-classification strategy[J].Acta Electronica Sinica,2008,36(8):1502-1507.(in Chinese)
[6]  J Weston,C Watikins.Multi-class Support Vector Machines .Technical Report CSD-TR-98-04,May 20,1998:1-10.
[7]  李阳阳,石洪竺,焦李成,马文萍.基于流形距离的量子进化聚类算法[J].电子学报,2011,39(10):2343-2347. LI Yang-yang,SHI Hong-zhu,JIAO Li-cheng,MA Wen-ping.Quantum-inspired evolutionary clustering algorithm based on manifold distance[J].Acta Electronica Sinica,2011,39(10):2343-2347.(in Chinese)
[8]  J A K Suykens,J Vandewalle.Least squares support vector machine classifiers[J].Neural Processing Letters,1999,9(3):293-300.
[9]  J R Quinlan.Induction of decision trees[J].Machine Learning,1996,1(1):81-106.
[10]  J R Quinlan.C4.5:Programs for Machine Learning[M].San Mateo,Calif:Morgan Kaufmann,1993.
[11]  J R Quinlan.Improved use of continuous attributes in C4.5.J[J].Artificial Intelligence Research,1996,4:77-99.
[12]  C A C Coello,G T Pulido,M S Lechuga.Handling multiple objectives with particle swarm optimization[J].IEEE Transactions on Evolutionary Computation,2004,8(3):256-279.
[13]  C Blake,E Keogh,C J Merz.UCI Repository of Machine Learning Databases .Department of Information and Computer Science,http://www.ics.uci.edu/~mlearn/MLRepository.html,1998.
[14]  李昆仑,黄厚宽,田盛丰.模糊多类SVM模型[J].电子学报,2004,32(5):830-832. LI Kun-lun,HUANG Hou-kuan,TIAN Sheng-feng.Fuzzy support vector machine for multi-class classification[J].Acta Electronica Sinica,2004,32(5):830-832.(in Chinese)
[15]  周伟达,张莉,焦李成.自适应支撑矢量机多用户检测[J].电子学报,2003,31(1):92-97. ZHOU Wei-da,ZHANG Li,JIAO Li-cheng.Adaptive SVM for multi-user detection[J].Acta Electronica Sinica,2003,31(1):92-97.(in Chinese)
[16]  W L Cai,S C Chen,D Q Zhang.A multiobjective simultaneous learning framework for clustering and classification[J].IEEE Transactions on Neural Networks,2010,21(2):185-200.
[17]  K Deb,A Pratap,S Agarwal,T Meyarivan.A fast and elitist multiobjective genetic algorithm:NSGA-II[J].IEEE Transactions on Evolutionary Computation,2002,6(2):182-197.
[18]  C C Chang,C J Lin.LIBSVM:A library for support vector machines,2001 .http://www.csie.ntu.edu.tw/~cjlin/libsvm.

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