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- W2380688867 abstract "In the research of support vector machines,with increasing the scale,some classification problems cannot be solved by the classical optimization methods.In order to design the training algorithms for large classification problems,an adaptive and iterative support vector machine algorithm based on chunk(CAISVM) is proposed.During the training process,the chunk incremental and decremental procedures are performed alternatively,and a small support vector set can be obtained adaptively.Six UCI(University of California-Irvine) data sets and Checkboard benchmark problem are tested,and comparisons between CAISVM and SVM~(Light) are given focusing on the number of support vectors.The simulating results show that,in general,the number of support vectors obtained by CAISVM is smaller than half of that obtained by SVM~(Light),in which more than 70 percent of the support vectors are included in the support vector set obtained by SVM~(Light),which shows that CAISVM is efficient in selecting the support vectors." @default.
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- W2380688867 date "2006-01-01" @default.
- W2380688867 modified "2023-09-28" @default.
- W2380688867 title "Study on Features of Support Vector Set of Adaptive and Iterative Algorithm" @default.
- W2380688867 hasPublicationYear "2006" @default.
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