支持向量机分类算法的若干研究.docxAbstractSupportVectorMachine(SVM)isamachinelearningmethodwithgoodperformance,,suchasdataming,patternrecognitionandthesignalprocessingetc,,suchastheconstructionofkernelfunction,theexistenceofnoiseandoutliers^andimbalanceddatasetsetc,,wemainlystudytheconstructionofthekernelfunctioninsupportvectormachine,theimprovementalgorithmofmembershipfunctioninfuzzysupportvectormachine,:(TrigonometricKernelScaling,TKS).TheTKSmethodnotonlyprovidesanewformofconformalmappingfunction,whichcanenrichetheconstructionofthekernelfunctionmethodsfromtheperspectiveofthegeometry,,,,anewundersamplingmethodispresentedtopreprocesstheimbalanceddatasetsjnordertoobtainbetterresult,thencostsensitivesupportvectormachineisusedtotrainpre-processeddatasets-:SupportVectorMachine,KernelFunction,ConfbmialTransformation,MembershipFunction,ImbalancedDatasets目录第一章绪论 11」课题背景及研究意义
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