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- W2365651442 abstract "Support Vector Machine(SVM) is a new machine learning technique developed based on statistical learning theory,and it is attracting increasing attentions.For machine learning tasks involving pattern classification,SVM has become an increasingly popular tool.The theory of SVM is studied at first,then an ameliorated RBF kernel function is presented,based on which an improved kernel function pattern classification method of SVM is put forward.Finally,simulation is made based on the IRIS data and the result is compared with the pattern classification result of FKNN,which shows that the ameliorated SVM outperforms the FKNN,with shorter operation time and is more suitable for real-time implementation." @default.
- W2365651442 created "2016-06-24" @default.
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- W2365651442 date "2007-01-01" @default.
- W2365651442 modified "2023-09-22" @default.
- W2365651442 title "An ameliorated pattern classification method of SVM" @default.
- W2365651442 hasPublicationYear "2007" @default.
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