Trend or No Trend

Trend or No Trend

ID:40984716

大小:1.08 MB

页数:68页

时间:2019-08-12

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1、TrendorNoTrend:ANovelNonparametricMethodforClassifyingTimeSeriesbyStanislavNikolovS.B.,MassachusettsInstituteofTechnology(2011)SubmittedtotheDepartmentofElectricalEngineeringandComputerScienceinpartialfulfillmentoftherequirementsforthedegreeofMasterofEngineeringinElectricalEngine

2、eringandComputerScienceattheMASSACHUSETTSINSTITUTEOFTECHNOLOGYSeptember2012cMassachusettsInstituteofTechnology2012.Allrightsreserved.Author..............................................................DepartmentofElectricalEngineeringandComputerScienceAugust15,2012Certifiedby....

3、......................................................Prof.DevavratShahJamiesonCareerDevelopmentAssociateProfessorofElectricalEngineeringandComputerScienceThesisSupervisorAugust15,2012Certifiedby..........................................................Dr.SatanjeevBanerjeeEnginee

4、r,TwitterInc.ThesisCo-SupervisorAugust15,2012Acceptedby.........................................................Prof.DennisM.FreemanChairman,MastersofEngineeringThesisCommittee2TrendorNoTrend:ANovelNonparametricMethodforClassifyingTimeSeriesbyStanislavNikolovSubmittedtotheDepart

5、mentofElectricalEngineeringandComputerScienceonAugust15,2012,inpartialfulfillmentoftherequirementsforthedegreeofMasterofEngineeringinElectricalEngineeringandComputerScienceAbstractInsupervisedclassification,oneattemptstolearnamodelofhowobjectsmaptolabelsbyselectingthebestmodelfrom

6、somemodelspace.Thechoiceofmodelspaceencodesassumptionsabouttheproblem.Weproposeasettingformodelspecificationandselectioninsupervisedlearningbasedonalatentsourcemodel.Inthissetting,wespecifythemodelbyasmallcollectionofunknownlatentsourcesandpositthatthereisastochasticmodelrelating

7、latentsourcesandobservations.Withthissettinginmind,weproposeanonparametricclassificationmethodthatisentirelyunawareofthestructureoftheselatentsources.Instead,ourmethodreliesonthedataasaproxyfortheunknownlatentsources.Weperformclassificationbycomputingtheconditionalclassprobabiliti

8、esforanobservationbasedonourstochasticmodel.Thi

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