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- W2368964600 abstract "Fitting function normally predict a relationship between variables by limited training samples of the trained function.In practice due to inherent noise and isolation of training samples,the results of fitting function often do not meet the requirements by using traditional methods.Considering the difference of feature's correlative degree to the regression problem becomes large,the support vector regression machine algorithm is researched,which uses the grey correlation grade as the feature weight.And extend in the application of the two-dimension functions fitting.The experiment resultal proves that this algorithm can get the better competence of regression fitting than the traditional support vector machine(SVR)." @default.
- W2368964600 created "2016-06-24" @default.
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- W2368964600 date "2012-01-01" @default.
- W2368964600 modified "2023-09-22" @default.
- W2368964600 title "Two-dimension functions fitting based on grey feature weighted support vector machine" @default.
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