粗糙集扩展模型及其在数据挖掘中的应用研究

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1、国防科学技术大学博士学位论文粗糙集扩展模型及其在数据挖掘中的应用研究姓名：赛英申请学位级别：博士专业：管理科学与工程指导教师：陈文伟2002.6.1国防科学技术大学研究生院学位论文ABSTRACTDataminingandknowledgediscoveryindatabasesisanewtechnologyfordrawingknowledgefromdata．Asaneffectiveapproachtoprocessingincomplete，impreciseoruncertaininformation,roughsethasbeenplay

2、inganimportantroleintheareaofdataminingandknowledgediscovery．Thesuccessfulapplicationsofroughsetapproachdependlargelyonthecompletenessofitstheory．Onlyafterthetheoryissystematicallyanddeeplystudied，callroughsetbeappliedtopracticaldomains：Takingasabackgroundtheprojectoftheresearch

3、ofnewtechnologyfordatawarehouseanddataminingintheareaofmanagementdecisionsupport，whichisgrantedbytheNationalNatureScienceFoundafion’thisthesisaddress．bscompletelyandsystematicallythemainresearchcontentsandmethodsofroughsetfromtheaspectsofboththeoryand印plication．Theprimarycontrib

4、utionsofthisthesis～include：‘Havingstudiedtheroughsettheorycarefully,thethesisfindstherelationshipbetweenroughsetandsuchabstracttheoriesasmodallogic，fuzzyset,algebrasystemandinterval-setalgebra,i．e．，roughsetprovidesawelldefinedsemanticalinterpretationtotheseabstracttheories，which

5、enablesUStobetterunderstandthem．Secondly,roughsetbuildsaninter-relationshipamongthesedependenttheoriesandconnectsthemtogether．～Thethesisstudiesthegeneralizedroughsetmodelsandproposesamulti-levelroughsetapproximationmodelCBM-RSbasedonacoveringoftheuniverse．Wevalidatethatthemulti-

6、levelroughsetapproximationinducedbyasequenceofreflexiverelationsisaspecialeaseofCBM-RS．CBM-RSmodelbreaksthroughthelimitofthemulti-levelroughsetmodelsinducedonlybybinaryrelations．Thethesisalsoexaminestheroughsetmodelbasedonclassificationaccoracy．TheMm-RSdataminingapproachgivenlat

7、erisbasedonthemodel．ThethesisproposesaroughsetapproachtominingminimalrulesininconsistentdecisiontablesMIE-RS．Wedealwiththeinconsistencythroughclassificationaccuracy,usingheuristicalgorithmswecangetasetofminimalproductiverulessatisfyingthegivenclassificationaccuracy．Withrespectto

8、theimplementofouralgorithm,weconstructtwoHashfu