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1、DataMiningtalrecording,centralizeddatawellsuitedtofind,eveniftheyaregoodCRISTINAOLARU,archives,andsoftwareandhard-expertsinthefield.Forexample,inLOUISWEHENKEL,waresimulationsmanypowersystemrelatedproblems,UniversityofLiggeDramaticcostdecreaseofmassstor-oneisfac
2、edwithhighdimensionaldataagedevicessetsthatcannotbeeasilymodeledandDataminingOM)isafolkloricdenom-Emergenceandquickgrowthofcontrolledonthewhole,and,therefore,inationofacomplexactivitythataimsfieldeddatabasemanagementsys-automaticmethodscapableofsynthe-atextract
3、ingsynthesizedandprevi-temssizingstructuresfromsuchdataouslyunknowninformationfromlargeAdvancesincomputertechnologybecomeanecessity.databases.Itdenotesalsoamultidisci-suchasfastercomputersandparal-Thistutorialpresentstheconceptofplinaryfieldofresearchanddevelop
4、-lelarchitecturesdataminingandaimsatprovidinganmentofalgorithmsandsoftwareContinuousdevelopmentsinauto-understandingoftheoverallprocessenvironmentstosupportthisactivitymaticlearningtechniquesandtoolsinvolved:howtheprocessinthecontextofreal-lifeproblemsPossiblep
5、resenceofuncertaintyinturnsout,whatcanbedonewithit,whereoftenhugeamountsofdataaredata(noise,outliers,missinginfor-whatarethemaintechniquesbehindit,availableformining.Thereisalotofmation).whicharetheoperationalaspects.WepublicityinthisfieldandalsodifferentThegen
6、eralpurposeofdataminingaimalsoatdescribingafewexampleswaystoseethethings.Hence,istoprocesstheinformationfromtheofdataminingapplications,soastodependingontheview-motivatethepowersystempoints,DMissometimesfieldasaveryopportuneconsideredasjustastepindataminingappl
7、ication.Forabroaderoverallprocessamorein-depthpresenta-calledknowledgediscoverytionofdataminingtoolsindatabases(KDD),orasaandtheirpossibleapplica-synonymofthelatteraswetionsinpowersystems,wedointhistutorial.Thus,inviteyoutohavealookataccordingtothislesstheForFu
8、rtherReadingpuristdefinition,DMsoft-section.wareincludestoolsofauto-maticlearningfromdata,DataMiningProcesssuchasmachinelearningBydefinition,dataminingis(ML)andartificialneu
