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DepartmentofComputerScience,UniversityofWaikato,NewZealandBernhardPfahringer(basedonmaterialbyEibeFrank,MarkHall,andPeterReutemann)WEKA:AMachineLearningToolkitTheExplorer•ClassificationandRegression•Clustering•AssociationRules•AttributeSelection•DataVisualizationTheExperimenterTheKnowledgeFlowGUIOtherUtilitiesConclusionsMachineLearningwithWEKA2011-3-25UniversityofWaikato2WEKA:thebirdCopyright:MartinKramer(mkramer@wxs.nl)TheWekaorwoodhen(Gallirallusaustralis)isanendemicbirdofNewZealand.(Source:WikiPedia)2011-3-25UniversityofWaikato3WEKA:thesoftwareMachinelearning/dataminingsoftwarewritteninJava(distributedundertheGNUPublicLicense)Usedforresearch,education,andapplicationsComplements“DataMining”byWitten&FrankMainfeatures:Comprehensivesetofdatapre-processingtools,learningalgorithmsandevaluationmethodsGraphicaluserinterfaces(incl.datavisualization)Environmentforcomparinglearningalgorithms2011-3-25UniversityofWaikato4HistoryProjectfundedbytheNZgovernmentsince1993Developstate-of-theartworkbenchofdataminingtoolsExplorefieldedapplicationsDevelopnewfundamentalmethods2011-3-25UniversityofWaikato5History(2)Late1992-fundingwasappliedforbyIanWitten1993-developmentoftheinterfaceandinfrastructureWEKAacronymcoinedbyGeoffHolmesWEKA’sfileformat“ARFF”wascreatedbyAndrewDonkinARFFwasrumoredtostandforAAndrew’sRRidiculousFFileFFormatSometimein1994-firstinternalreleaseofWEKATCL/TKuserinterface+learningalgorithmswrittenmostlyinCVerymuchbetasoftwareChangesfortheb1releaseincluded(amongothers):“AmbiguousandUnsupportedmenucommandsremoved.”“Crashingprocesseshandled(inmostcases:-)”October1996-firstpublicrelease:WEKA2.12011-3-25UniversityofWaikato6History(3)July1997-WEKA2.2Schemes:1R,T2,K*,M5,M5Class,IB1-4,FOIL,PEBLS,supportforC5Includedafacility(basedonUnixmakefiles)forconfiguringandrunninglargescaleexperimentsEarly1997-decisionwasmadetorewriteWEKAinJavaOriginatedfromcodewrittenbyEibeFrankforhisPhDOriginallycodenamedJAWS(JAJAvaWWekaSSystem)May1998-WEKA2.3LastreleaseoftheTCL/TK-basedsystemMid1999-WEKA3(100%Java)releasedVersiontocomplementtheDataMiningbookDevelopmentversion(includingGUI)2011-3-25UniversityofWaikato7TheGUIbackthen…TCL/TKinterfaceofWeka2.12011-3-25UniversityofWaikato8WEKA:versionsThereareseveralversionsofWEKA:WEKA3.4:“bookversion”compatiblewithdescriptionindataminingbookWEKA3.5.5:“developmentversion”withlotsofimprovementsThistalkisbasedonanightlysnapshotofWEKA3.5.5(12-Feb-2007)2011-3-25UniversityofWaikato9@relationheart-disease-simplified@attributeagenumeric@attributesex{female,male}@attributechest_pain_type{typ_angina,asympt,non_anginal,atyp_angina}@attributecholesterolnumeric@attributeexercise_induced_angina{no,yes}@attributeclass{present,not_present}@data63,male,typ_angina,233,no,not_present67,male,asympt,286,yes,present67,male,asympt,229,yes,present38,female,non_anginal,?,no,not_present...WEKAonlydealswith“flat”files2011-3-25UniversityofWaikato10@relationheart-disease-simplified@attributeagenumeric@attributesex{female,male}@attributechest_pain_type{typ_angina,asympt,non_anginal,atyp_angina}@attributecholesterolnumeric@attributeexercise_induced_angina{no,yes}@attributeclass{present,not_present}@data63,male,typ_angina,233,no,not_present67,male,asympt,286,yes,present67,male,asympt,229,yes,present38,female,non_anginal,?,no,not_present...WEKAonlydealswith“flat”files2011-3-25UniversityofWaikato11javaweka.gui.GUIChooser2011-3-25UniversityofWaikato122011-3-25UniversityofWaikato132011-3-25UniversityofWaikato14java-jarweka.jar2011-3-25UniversityofWaikato15Explorer:pre-processingthedataDatacanbeimportedfromafileinvariousformats:ARFF,CSV,C4.5,binaryDatacanalsobereadfromaURLorfromanSQLdatabase(usingJDBC)Pre-processingtoolsinWEKAarecalled“filters”WEKAcontainsfiltersfor:Discretization,normalization,resampling,attributeselection,transformingandcombiningattributes,…2011-3-25UniversityofWaikato162011-3-25UniversityofWaikato172011-3-25UniversityofWaikato182011-3-25UniversityofWaikato192011-3-25UniversityofWaikato202011-3-25UniversityofWaikato212011-3-25UniversityofWaikato222011-3-25UniversityofWaikato232011-3-25UniversityofWaikato242011-3-25UniversityofWaikato252011-3-25UniversityofWaikato262011-3-25UniversityofWaikato272011-3-25UniversityofWaikato282011-3-25UniversityofWaikato292011-3-25UniversityofWaikato302011-3-25UniversityofWaikato312011-3-25UniversityofWaikato322011-3-25UniversityofWaikato332011-3-25UniversityofWaikato342011-3-25UniversityofWaikato352011-3-25UniversityofWaikato362011-3-25UniversityofWaikato37Explorer:building“classifiers”ClassifiersinWEKAaremodelsforpredictingnominalornumericquantitiesImplementedlearningschemesinclude:Decisiontreesandlists,instance-basedclassifiers,supportvectormachines,multi-layerperceptrons,logisticregression,Bayes’nets,…“Meta”-classifiersinclude:Bagging,boosting,stacking,error-correctingoutputcodes,locallyweightedlearning,…2011-3-25UniversityofWaikato382011-3-25UniversityofWaikato392011-3-25UniversityofWaikato402011-3-25UniversityofWaikato412011-3-
本文标题:Weka_a_tool_for_exploratory_data_mining
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