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1、ThispageintentionallyleftblankKernelMethodsforPatternAnalysisPatternAnalysisistheprocessoffindinggeneralrelationsinasetofdata,andformsthecoreofmanydisciplines,fromneuralnetworkstoso-calledsyn-tacticalpatternrecognition,fromstatisticalpatternrecognitiontomachinelearninganddatamining.Application
2、sofpatternanalysisrangefrombioin-formaticstodocumentretrieval.Thekernelmethodologydescribedhereprovidesapowerfulandunifiedframeworkforallofthesedisciplines,motivatingalgorithmsthatcanactongeneraltypesofdata(e.g.strings,vectors,text,etc.)andlookforgeneraltypesofrelations(e.g.rankings,classificat
3、ions,regressions,clusters,etc.).Thisbookfulfilstwomajorroles.Firstlyitprovidespractitionerswithalargetoolkitofalgorithms,kernelsandsolutionsreadytobeimplemented,manygivenasMatlabcodesuitableformanypatternanalysistasksinfieldssuchasbioinformatics,textanalysis,andimageanalysis.Secondlyitfurnishes
4、studentsandresearcherswithaneasyintroductiontotherapidlyexpandingfieldofkernel-basedpatternanalysis,demonstratingwithexampleshowtohandcraftanalgorithmorakernelforanewspecificapplication,whilecoveringtherequiredconceptualandmathematicaltoolsnecessarytodoso.Thebookisinthreeparts.Thefirstprovidesth
5、econceptualfoundationsofthefield,bothbygivinganextendedintroductoryexampleandbycov-eringthemaintheoreticalunderpinningsoftheapproach.Thesecondpartcontainsanumberofkernel-basedalgorithms,fromthesimplesttosophis-ticatedsystemssuchaskernelpartialleastsquares,canonicalcorrelationanalysis,supportve
6、ctormachines,principalcomponentsanalysis,etc.Thefinalpartdescribesanumberofkernelfunctions,frombasicexamplestoadvancedrecursivekernels,kernelsderivedfromgenerativemodelssuchasHMMsandstringmatchingkernelsbasedondynamicprogramming,aswellasspecialkernelsdesignedtohandletextdocuments.Allthoseinvol
7、vedinpatternrecognition,machinelearning,neuralnet-worksandtheirapplications,fromcomputationalbiologytotextanalysiswillwelcomethisaccount.KernelMethodsforPatternAnalysisJohnShawe-TaylorUniversityofSouthamptonNelloCristianiniUniversityofCalifor
