SVM Aggregating Intelligence

Description:

SVM Aggregating Intelligence is a set of methodologies and approaches to collect computing intellect of multiple SVMs through construction of SVM based multi-core complex system to which single SVM methodologies and approaches are ineffective or infeasible. In this field,we developed early several SVM modular aggregations,such as random SVM mixture expert system,SVM Ensemble; ordered SVM aggregation system,SVM Classification Trees (SVMT); SVMT association rule mining system rSVMT,and personalized transductive learning SVMT,ptSVMT.

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Related articles:

• S. Pang,D. Kim and S.Y. Bang,"Face membership authentication using SVM classification tree generated by membership-based LLE data partition," IEEE Transactions on Neural Networks,vol. 16,no. 2,pp. 436 -446,2005.|PDF|Bibtxt|
• S. Pang,"Constructing SVM Multiple Tree for Face Membership Authentication," Biometric Authentication,vol. 3072,pp. 1-13,Springer Berlin / Heidelberg,2004.|PDF|Bibtxt|
• S. Pang,"Membership authentication in the dynamic group by face classification using SVM ensemble," Pattern Recognition Letters,vol. 24,no. 1-3,pp. 215 - 225,2003.|PDF|Bibtxt|
• H. C. Kim,S. Pang,H. M. Je,D. Kim and S. Y. Bang,"Constructing support vector machine ensemble," Pattern Recognition,vol. 36,no. 12,pp. 2757 - 2767,2003.|PDF|Bibtxt|
• S. Pang,T. Ban,Y. Kadobayashi and N. Kasabov,"Personalized mode transductive spanning SVM classification tree," Information Sciences,vol. 181,no. 11,pp. 2071 - 2085,2011.|PDF|Bibtxt|
• S. Pang and N. Kasabov,"Encoding and decoding the knowledge of association rules over SVM classification trees," Knowledge and Information Systems,vol. 19,no. 1,pp. 79-105,2009.|PDF|Bibtxt|